Evidence map›Paper›PMID 40741046›Full record

ArticleFrontiers in aging neuroscience2025

Brain structural MRI marker for predicting conversion to Parkinson's disease in individuals with prodromal symptoms.

Chang-Hyun Park, Uicheul Yoon, Phil Hyu Lee, Jinna Kim, Seung-Koo Lee, Na-Young Shin

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Chang-Hyun ParkDivision of Artificial Intelligence and Software, College of Artificial Intelligence, Ewha Womans University, Seoul, Republic of Korea.
Uicheul YoonDepartment of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Gyeongsan, Republic of Korea.
Phil Hyu LeeDepartment of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jinna KimDepartment of Radiology, Research Institute of Radiological Science, and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
Seung-Koo LeeDepartment of Radiology, Research Institute of Radiological Science, and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
Na-Young ShinDepartment of Radiology, Research Institute of Radiological Science, and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During the prodromal stage of Parkinson's disease (PD), brain structural alterations precede clinical diagnosis and offer opportunities for early detection. We investigated whether combining clinical non-motor markers with an MRI-based brain structural marker could enhance predictive performance for PD conversion. Methods: Individuals with prodromal symptoms ( Results: Six individuals converted to PD within 4 years. The MRI marker classified 21 individuals as having PD-like brain patterns, including all six converters. When combined with olfactory dysfunction, the approach achieved optimal performance with 100% sensitivity, 80% specificity, and 90% balanced accuracy, outperforming individual markers and other combinations. Conclusion: MRI-quantified brain structural similarity to PD, particularly when combined with olfactory assessment, significantly enhances prediction of PD conversion in individuals with prodromal symptoms. This accessible, multimodal approach could facilitate early identification of high-risk individuals for targeted interventions and clinical trials.

Indexed as

machine learningMRIolfactory dysfunctionParkinson’s diseaseprodromal symptomrapid eye movement sleep behavior disorder

Identifiers

PMID40741046
PMCPMC12307297

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.