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Record W4409033722 · doi:10.1186/s13550-025-01216-8

Autoradiographic comparison between [11C]PiB and [18F]AZD4694 in human brain tissue

2025· article· en· W4409033722 on OpenAlexafffund
Antonio Aliaga, Joseph Therriault, Kely Quispialaya, Arturo Aliaga, Peter Kunach, Arthur C. Macedo, Robert Hopewell, Nesrine Rahmouni, Jean-Paul R. Soucy, Gassan Massarweh, Marie-Christine Guiot, Tevy Chan, Jesse Klostranec, Aida Mary Abreu Diaz, Andréia Silva da Rocha, Giovanna Carello‐Collar, Luiza Santos Machado, Marco Antônio De Bastiani, Débora Guerini de Souza, Diogo O. Souza, Aline Rigon Zimmer, Serge Gauthier, Tharick A. Pascoal, Eduardo R. Zimmer, Pedro Rosa‐Neto

Bibliographic record

VenueEJNMMI Research · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité de MontréalMcGill University Health CentreMcGill UniversityDouglas Mental Health University InstituteMontreal Neurological Institute and Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchFondation Brain CanadaConsortium canadien en neurodégénérescence associée au vieillissementAlzheimer's Association
KeywordsPosterior cingulatePittsburgh compound BMedicineHuman brainWhite matterHippocampal formationCortex (anatomy)PathologyAmyloid (mycology)HippocampusPositron emission tomographyPrefrontal cortexNuclear medicineAlzheimer's diseaseNeuroscienceMagnetic resonance imagingInternal medicineBiologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Amyloid-β imaging through positron emission tomography (PET) has significantly transformed Alzheimer’s disease (AD) research. [ 11 C]PiB has been widely used for imaging β-amyloid plaques due to its high affinity and selectivity for amyloid deposits. [ 18 F]AZD4694 is a more recently developed amyloid-PET imaging agent, which structurally resembles PiB and has less non-specific binding in the white matter than other 18 F-labeled compounds. The purpose of this study is to compare the in vitro binding properties of the amyloid-PET radiotracers [ 11 C]PiB and [ 18 F]AZD4694 in post-mortem human brain tissue. Total binding was assessed by autoradiography in prefrontal, inferior parietal, posterior cingulate cortices and hippocampal sections of healthy control (HC) and AD autopsy-confirmed brain tissues. Furthermore, the displacement of [ 18 F]AZD4694 by unlabeled PiB was evaluated in the above-mentioned sections of AD brain tissues. Results For both radiotracers, we found significant differences (p < 0.0001) between HC and AD tissues binding in the prefrontal cortex ([ 11 C]PiB Cohen’s d = 3.424, [ 18 F]AZD4694 Cohen’s d = 5.070), inferior parietal cortex ([ 11 C]PiB Cohen’s d = 3.156, [ 18 F]AZD4694 Cohen’s d = 3.959), posterior cingulate cortex ([ 11 C]PiB Cohen’s d = 1.781, [ 18 F]AZD4694 Cohen’s d = 3.434), and hippocampus ([ 11 C]PiB Cohen’s d = 1.320, [ 18 F]AZD4694 Cohen’s d = 3.696). Higher binding was detected for [ 18 F]AZD4694 compared to [ 11 C]PiB in AD prefrontal, inferior parietal and posterior cingulate cortices, while binding in the hippocampus was comparable for both radioligands. Strong correlations between [ 18 ]AZD4694 and [ 11 C]PiB were found in the prefrontal (R = 0.959, p < 0.0001), inferior parietal (R = 0.893, p < 0.0001), posterior cingulate (R = 0.838, p = 0.0006) cortices and hippocampus (R = 0.750, p < 0.0001). Bland–Altman analyses revealed strong agreement between [ 11 C]PiB and [ 18 F]AZD4694 in the prefrontal, inferior parietal, and posterior cingulate cortices, but lower agreement in the hippocampus. Displacement studies confirmed high binding affinity of PiB in all tissues, indicating that both amyloid-PET agents compete for the same binding sites. Conclusions This head-to-head study provides evidence that while [ 18 F]AZD4694 and [ 11 C]PiB bindings are highly correlated with both tracers competing for the same binding sites, [ 18 F]AZD4694 has a slightly higher effect size when comparing between neuropathologically-confirmed AD and HC brain tissues.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.106
GPT teacher head0.499
Teacher spread0.393 · 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 teacher head, 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".

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Citations5
Published2025
Admission routes2
Has abstractyes

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