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Record W4410933271 · doi:10.1002/jmri.29832

Association of Myelin Disruption and Iron Accumulation on <scp>MRI</scp> With Parkinson's Disease Severity

2025· article· en· W4410933271 on OpenAlexaboutno aff
Xiaolu Li, Shuting Bu, Huize Pang, Hongmei Yu, Mengwan Zhao, Juzhou Wang, Yueluan Jiang, Mathias Nittka, Yang Liu, Guoguang Fan

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2025
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsWhite matterQuantitative susceptibility mappingMedicineParkinson's diseaseInternal medicineAtrophyMyelinPopulationGastroenterologyCingulum (brain)Magnetic resonance imagingPathologyNuclear medicinePsychologyDiseaseRadiologyCentral nervous system

Abstract

fetched live from OpenAlex

BACKGROUND: Myelin degeneration and iron accumulation are key features of Parkinson's disease (PD), yet their interrelationship and contribution to disease severity remain unclear. PURPOSE: To assess alterations in myelin content and iron deposition in PD, investigate their interrelationship and associations with disease severity. STUDY TYPE: Retrospective. POPULATION: Fifty-three PD patients (27 females; median age 67 years) and 30 age- and sex-matched healthy controls (HCs) (14 females; median age 64 years). FIELD STRENGTH/SEQUENCE: 3-T, two-dimensional section-selective steady-state free precession for MR fingerprinting, three-dimensional multiecho gradient-recalled echo for quantitative susceptibility mapping (QSM), and 3D T1-weighted gradient echo sequence. ASSESSMENT: Cognitive impairment was evaluated using the Montreal Cognitive Assessment (MoCA), while motor dysfunction was evaluated with the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III). Thirty-five white and gray matter regions of interest (ROIs) were defined using the MNI atlas. Myelin water fraction (MWF) was quantified using multicomponent relaxometry, and iron deposition was assessed via QSM. STATISTICAL TESTS: Voxel-wise comparisons were performed between PD and HCs. Stepwise regression analyses explored associations between significantly altered imaging metrics and disease severity. A corrected p < 0.05 was considered statistically significant. RESULTS: PD patients showed significantly reduced MWF and increased susceptibility in multiple predefined ROIs. MoCA scores were significantly associated with MWF and T1 in the left thalamus (β = 104.213; β = -0.015), and susceptibility in the left thalamic radiation (β = -107.346). MDS-UPDRS III scores were significantly associated with MWF in the contralateral uncinate fasciculus (β = -130.751) and susceptibility in the internal capsule (β = 267.798). Notably, MWF in the right internal capsule (β = -0.213) and nucleus accumbens (β = -0.302), and T1 in the right internal capsule (β = 0.001) were significantly correlated with susceptibility. DATA CONCLUSION: This study may provide quantitative evidence of myelin loss and iron accumulation in PD. The observed associations between MRF, susceptibility, and disease severity could offer insights into PD pathophysiology. LEVEL OF EVIDENCE: 2: Technical Efficacy: Stage 1.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.273
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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