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Record W2981047442 · doi:10.1016/j.jalz.2019.06.3460

P3‐426: REGIONAL AND VOXEL‐WISE SPATIAL RELATIONSHIPS AMONG FLUORINE‐18 AMYLOID PET TRACERS AND PITTSBURGH COMPOUND B

2019· article· en· W2981047442 on OpenAlexaff
Shaney Flores, Yi Su, Brian A. Gordon, Adedamola Adedokun, Laura M. Marple, Qing Wang, Gengsheng Chen, Russ C. Hornbeck, Clifford R. Jack, Erik D. Roberson, Jean‐Paul Soucy, Richard B. Noto, William S. Brooks, Ivonne Z. Jiménez‐Velázquez, Serge Gauthier, Ging‐Yuek Robin Hsiung, Ghulam M. Surti, Martin R. Farlow, Stephen Salloway, Eric McDade, Randall J. Bateman, Tammie L.S. Benzinger

Bibliographic record

VenueAlzheimer s & Dementia · 2019
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsMcGill University Health CentreUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsPittsburgh compound BNuclear medicineWhite matterVoxelGrey matterMedicineAlzheimer's diseasePathologyPsychologyMagnetic resonance imagingDiseaseRadiology

Abstract

fetched live from OpenAlex

Historically, the spatial spread of amyloid plaques in studies of Alzheimer's disease (AD) has been quantified with the radioligand [11C]Pittsburgh Compound B (PiB). However, its short half-life limits its viability in clinical and research settings without direct access to radiochemical facilities. [18F]-radioligands, such as florbetapir, florbetaben, and NAV4694, were developed to address this issue but questions remain concerning their comparability to PiB. Using data from two sporadic AD cohorts in the Centiloid project (NAV4694 and florbetaben) and an autosomal AD cohort (florbetapir), we investigated each [18F] tracer's relationship to PiB. PET and T1-weighted head MR images for healthy controls and AD patients were downloaded from the Centiloid project and the Dominantly Inherited Alzheimer's Network-Trial Unit. PET scans using each [18F] tracer were acquired within three months from PiB. MR images were segmented into cortical and subcortical regions of interest (ROIs) using FreeSurfer-5.3. Standard uptake value ratios (SUVrs) were calculated from 90–110 minutes post-injection for florbetaben, and 50–70 minutes post-injection for all other tracers, using cerebellar grey as a reference region. SUVrs between [18F] tracers and PiB were correlated at the ROI level (for cortical/subcortical grey only, and cortical/subcortical grey and subcortical white matter) and at the voxel-wise level. Similarity to PiB across the [18F] tracers was assessed using pairwise t-tests on Fisher's z-transformed values. NAV4694 had the highest correlation with PiB (r=0.95) than either florbetapir (r=0.85) or florbetaben (r=0.90) for cortical and subcortical grey matter (Figure 1). For comparison, PiB test-retest data from a previous report1 showed a regional spatial correlation of >0.91 for cortical and subcortical grey matter. This pattern persisted at the voxel-wise level (Figure 2; NAV4694: r=0.90, florbetapir: r=0.87, florbetaben: r=0.88). Florbetaben showed a significantly stronger relationship with PiB than florbetapir but only at the ROI level.

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 score0.005
Threshold uncertainty score0.010

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)0.0020.001

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 head0.048
GPT teacher head0.291
Teacher spread0.244 · 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
Published2019
Admission routes1
Has abstractyes

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