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Related Experiment Video

Updated: Jul 17, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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Nuclear Imaging Data-Driven Classification of Parkinson's Disease.

Tomoko Totsune1,2, Toru Baba1, Yoko Sugimura1,3

  • 1Department of Neurology, National Hospital Organization Sendai-Nishitaga Hospital, Sendai, Japan.

Movement Disorders : Official Journal of the Movement Disorder Society
|August 28, 2023
PubMed
Summary

Nuclear imaging identified distinct Parkinson's disease (PD) subtypes. These subtypes, cardio-cortical impairment (CC) and dopaminergic-dominant dysfunction (DD), show different disease progression and cortical atrophy patterns.

Keywords:
FP-CITMIBGParkinson's diseaseVBMdisease subtype

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Area of Science:

  • Neurology
  • Nuclear Medicine
  • Neuroimaging

Background:

  • Parkinson's disease (PD) is a complex neurodegenerative disorder with varied motor and non-motor symptoms.
  • Clinical subtypes of PD exist, but their classification based on symptoms lacks stability.
  • Prognostic features are crucial for understanding PD heterogeneity.

Purpose of the Study:

  • To classify Parkinson's disease (PD) subtypes using nuclear imaging biomarkers.
  • To investigate cardiac sympathetic nervous and nigro-striatal systems in PD.
  • To compare cortical morphological changes across identified PD subtypes.

Main Methods:

  • Hierarchical cluster analysis of 56 PD patients' imaging data.
  • Utilized 123I-metaiodobenzylguanidine cardiac scintigraphy and 123I-N-(3-fluoropropyl)-2β-carbomethoxy-3β-(4-iodophenyl) nortropane SPECT.
  • Compared clinical features and cortical atrophy patterns among clusters.

Main Results:

  • Identified three clusters, leading to two subtypes: cardio-cortical impairment (CC) and dopaminergic-dominant dysfunction (DD).
  • Subtypes differed in onset age and need for dopamine therapy or deep brain stimulation.
  • Early CC subtype showed parietal-dominant cortical atrophy; advanced DD showed left-sided atrophy.

Conclusions:

  • Nuclear imaging biomarkers enable classification of clinically and pathologically relevant PD subtypes.
  • Identified subtypes exhibit distinct disease trajectories and patterns of neurodegeneration.
  • This approach aids in understanding PD heterogeneity and progression.