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Record W4390197039 · doi:10.1002/alz.081879

In vivo data‐driven patterns of Tau accumulation associated with AD progression using 18F‐MK‐6240 PET

2023· article· en· W4390197039 on OpenAlexaffabout
Vladimir Fonov, Tahnia Nazneen, Pedro Rosa‐Neto, D. Louis Collins

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsStandardized uptake valueTemporal lobeDementiaPositron emission tomographyNeuroscienceCognitive impairmentPartial volumePathologyAlzheimer's diseasePsychologyNuclear medicineMedicineCognitionDisease

Abstract

fetched live from OpenAlex

Abstract Background Alzheimer’s disease is a neurodegenerative disease associated with accumulation of amyloid beta and tau neurofibrillary tangles following a pattern known as Braak stages (Braak 1995,2011). Recent papers (Pascoal 2020) indicate possibility to recapitulate Braak histo‐pathological stages in vivo using tau tangles PET tracer 18F‐MK‐6240, using manually defined regions of interest. This study analyzes patterns of Tau accumulation associated with AD in a completely data‐driven fashion. Method We used T1w MRI and 18F‐MK‐6240 Pet scans from healthy controls in the community or outpatients at the McGill University Research Centre for Studies in Aging. The following number of datasets from each diagnostic group [n scans total (m unique participants)]: cognitively normal: 347(194), mild cognitive impairment: 163(99), Alzheimer’s disease dementia: 114(77). T1w MRIs were pre‐processed (non‐uniformity correction, intensity normalization, stereotaxic registration, brain masking, tissue classification); FALCON (Fonov 2020) was used to extract the mid‐cortical surface. PET scans were linearly registered to the T1w MRI and the standardized uptake value ratio (SUVR) was calculated using whole cerebellum grey matter as the reference. SUVR values were sampled along cortical mid‐surfaces and geodesically smoothed with a 10mm gaussian and resampled to the cortical surface of MNI2009c template (Fonov 2011). Result Figure 1 shows Mean SUVR values on top of Figure 1, and latent factors at the bottom. Overall low values of tau in the temporal, partial and occipital region are associated with normal cognition (F1). Tau changes in the temporal lobe (F2, similar to stage 1&2) are associated with a slight cognitive change. Change in parietal and posterior temporal areas (F3, similar to stage 3&4) are associated with even more cognitive loss. Finally changes in the motor strip and ventral portion of the occipital lobe and remaining cortex (F4 and F5) are associated with the very advanced stages (5&6) of cognitive decline. Conclusion We discovered patterns of tau accumulation associated with progression of cognitive decline in a completely data‐driven fashion.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.192
GPT teacher head0.431
Teacher spread0.239 · 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

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