Temporal trajectory model for dopaminergic input to the striatal subregions in Parkinson's disease

Han Kyeol Kim, Myung Jun Lee, Han Soo Yoo, Jae Hoon Lee, Young Hoon Ryu, Chul Hyoung Lyoo

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Almost half of the nigral neurons are already lost during the preclinical period of Parkinson's disease (PD), and then the speed of neuronal loss is slowly attenuated during the subsequent progression. We sought to establish long-term temporal trajectory models for the dopaminergic input to the striatal subregions and a 4D-temporal trajectory model for the dopamine transporter positron emission tomography (PET). Methods: We selected 83 patients in PD spectrum who underwent dopamine transporter PET scan twice and 71 age-matched healthy controls. We created temporal trajectories of specific binding ratios of the striatal subregions by integrating function between baseline values and their annual change rates and also created 4D-temporal trajectory model by applying the same method for each striatal voxel. Using the PET data of additional 100 PD patients, we estimated an individual time point in the 4D-temporal trajectory model for the validation. Results: Degenerative loss of striatal dopaminergic input first appeared in the posterior dorsal putamen in the more affected side at 14.4 years before the clinical onset, and subsequently in the posterior ventral and anterior putamen, and finally in the caudate. The time delay between the initiation of dopaminergic loss in the more and less affected posterior dorsal putamen was 6.1 years. The estimated individual time points within the entire disease course were correlated with the motor severity. Conclusion: Our temporal trajectory model demonstrated a sequential loss of dopaminergic input in the striatal subregions in PD and may be beneficial for the evaluation of individual status of disease progression.

Original languageEnglish
Pages (from-to)42-49
Number of pages8
JournalParkinsonism and Related Disorders
Volume103
DOIs
Publication statusPublished - 2022 Oct

Bibliographical note

Funding Information:
This research was supported by a faculty research grant of Yonsei University College of Medicine ( 6-2021-0094 ).

Publisher Copyright:
© 2022 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Neurology
  • Geriatrics and Gerontology
  • Clinical Neurology

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