MétaCan
Menu
← Back to cohort
Record W4387131136 · doi:10.21203/rs.3.rs-3392867/v1

Uncovering the Neuroanatomical Signature of the Transition from Normal Cognition to Mild Cognitive Impairment in Parkinson's Disease: A VBM and Brain Age Estimation Study

2023· preprint· en· W4387131136 on OpenAlexafffund
Iman Beheshti, Jarrad Perron, Ji Hyun Ko

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Manitoba
FundersEngineering and Physical Sciences Research CouncilAvid RadiopharmaceuticalsParkinson CanadaBiogenBristol-Myers Squibb
KeywordsCognitionCognitive declineVoxel-based morphometryNeuroimagingWhite matterGrey matterParkinson's diseaseCerebellumVoxelMedicineNeurosciencePsychologyCognitive impairmentAudiologyInternal medicineCardiologyMagnetic resonance imagingDiseaseDementiaRadiology

Abstract

fetched live from OpenAlex

Abstract The progression of Parkinson’s disease (PD) is often accompanied by cognitive decline. This study aims to uncover neuroanatomical indicators of the transition from healthful cognition to mild cognitive impairment (MCI) in PD using brain age estimation methodologies and structural neuroimaging data. Structural MRI data for 244 subjects from the Parkinson Progression Markers Initiative (PPMI) was acquired. 192 of these were PD patients with stable healthy cognitive function from baseline out to 5 years (PD-SHC), and as the remaining 52 were PD patients who had unstable healthy cognition and developed MCI within 5 years (PD-UHC). We conducted voxel-based morphometry (VBM), deformation-based morphometry, and cortical thickness analyses to measure structural brain differences between these groups at baseline and to assess any differences in brain aging. The VBM analysis revealed that PD-SHC patients have larger grey matter volumes compared to PD-UHC subjects at baseline. This difference was located entirely within the cerebellum with significant clusters found within the posterior and anterior lobes and on the declive and culmen regions of the vermis. No differences were observed in the white matter, local brain tissue volumetry or cortical thickness measurements between the two groups. At baseline, PD-UHC patients exhibited significantly greater brain aging than PD-SHC patients (mean difference = 3.24 years, Cohen’s d = 0.43; t(242) = 2.78, p = 0.005). Our analysis provides an in-depth understanding of the neuroanatomical signatures of cognitive decline in PD by demonstrating the role of the cerebellum as a site of early anatomical change that accompanies the transition from healthy cognition to MCI. This could aid in elucidating further changes along the structural-functional continuum which accompany this cognitive transition, serve as a biomarker of the earliest form of cognitive decline in patients with PD and enrich trials of cognitive intervention in this patient population.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.043
GPT teacher head0.362
Teacher spread0.319 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueResearch Square→Same topicParkinson's Disease Mechanisms and Treatments→French-language works237,207→