Automated assessment of susceptibility map-weighted imaging in patients with clinically uncertain parkinsonism

Feb. 2026

Background and objectives: In patients with a clinically uncertain parkinsonian syndrome (CUPS), the novel MRI sequence susceptibility map-weighted imaging (SMWI) may be a diagnostic alternative to dopamine transporter (DAT) imaging with the advantage of greater accessibility. This study aimed to assess the diagnostic accuracy of software analyzing SMWI in differentiating dopaminergic neurodegenerative from non-neurodegenerative parkinsonism in CUPS patients.

Methods: A diagnostic accuracy study was conducted, including patients presenting with CUPS who underwent DAT SPECT imaging. The index test was the result of AI-driven software (Heuron IPD version 1.0.1.9, Heuron Co., Ltd, Seoul, Korea), designed to classify the nigrosome-1 on SMWI acquired at 3T as normal or abnormal. The reference test was the final clinical diagnosis, incorporating findings from DAT SPECT imaging.

Results: A total of 176 patients were included in the final analysis; 82 received a final diagnosis of dopaminergic neurodegenerative parkinsonism, and 94 with non-neurodegenerative parkinsonism. The AI-driven SMWI soft ware demonstrated a diagnostic accuracy of 86.9 % distinguishing neurodegenerative from non- neurodegenerative parkinsonism, with sensitivity of 92.7 % and specificity of 81.9 %.

Discussion: This study is the first to evaluate the diagnostic accuracy of software analyzing SMWI in patients presenting with CUPS. The findings highlight the promising diagnostic utility of SMWI in clinical practice for CUPS patients. Future studies are warranted as SMWI might be able to reduce the need for DAT-imaging in the future by offering a more accessible and cost-effective alternative

  • Link

    https://doi.org/10.1016/j.parkreldis.2026.108198
  • Author

    Elon D. Wallerta, Elsmarieke van de Giessenb, Martijn Beudelc, Tom van Mierlod, Jeroen Blankevoorte, Henk W. Berendsef, Rob M.A. de Biec, Jan Booija
  • Keywords

    Magnetic resonance imaging, Susceptibility map-weighted imaging, Automated assessment, Clinically uncertain parkinsonian syndrome, Parkinson's disease
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