MétaCan
Menu
Back to cohort
Record W3042249111 · doi:10.1212/wnl.0000000000010256

Multitracer model for staging cortical amyloid deposition using PET imaging

2020· article· en· W3042249111 on OpenAlexfundno aff
Lyduine E. Collij, Fiona Heeman, Gemma Salvadó, Silvia Ingala, Daniele Altomare, Arno de Wilde, Elles Konijnenberg, Marieke van Buchem, Maqsood Yaqub, Paweł Markiewicz, Sandeep S.V. Golla, Viktor Wottschel, Alle Meije Wink, Pieter Jelle Visser, Charlotte E. Teunissen, Adriaan A. Lammertsma, Philip Scheltens, Wiesje M. van der Flier, Ronald Boellaard, Bart N.M. van Berckel, José Luís Molinuevo, Juan Domingo Gispert, Mark E. Schmidt, Frederik Barkhof, Isadora Lopes Alves, Eider M. Arenaza‐Urquijo, Annabella Beteta, Anna Brugulat‐Serrat, Raffaele Cacciaglia, Alba Cañas Boccagni, Yelena G. Bodien, Marta Crous‐Bou, Carme Deulofeu, Ruth Dominguez, Karine Fauria, Carles Falcón, Marta Félez‐Sánchez, José María González de Echavarri, Oriol Grau‐Rivera, Laura L. Hernandez, Gema Huesa, Jordi Huguet, María León, Paula Marne, Tania Menchón, Marta Milà‐Alomà, Grégory Operto, Carolina Minguillón, María Pascual, Albina Polo, Sandra Pradas, Aleix Sala‐Vila, Gonzalo Sánchez‐Benavides, Mahnaz Shekari, Anna Soteras, Marc Suárez‐Calvet, Laia Tenas, Marc Vilanova, Natàlia Vilor‐Tejedor

Bibliographic record

VenueNeurology · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Biomedical Imaging and BioengineeringNational Institute on AgingNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchZonMw
KeywordsAmyloid (mycology)PathologyMedicineDeposition (geology)NeuroimagingNuclear medicineNeurosciencePsychologyBiology

Abstract

fetched live from OpenAlex

<h3>Objective</h3> To develop and evaluate a model for staging cortical amyloid deposition using PET with high generalizability. <h3>Methods</h3> Three thousand twenty-seven individuals (1,763 cognitively unimpaired [CU], 658 impaired, 467 with Alzheimer disease [AD] dementia, 111 with non-AD dementia, and 28 with missing diagnosis) from 6 cohorts (European Medical Information Framework for AD, Alzheimer9s and Family, Alzheimer9s Biomarkers in Daily Practice, Amsterdam Dementia Cohort, Open Access Series of Imaging Studies [OASIS]-3, Alzheimer’s Disease Neuroimaging Initiative [ADNI]) who underwent amyloid PET were retrospectively included; 1,049 individuals had follow-up scans. With application of dataset-specific cutoffs to global standard uptake value ratio (SUVr) values from 27 regions, single-tracer and pooled multitracer regional rankings were constructed from the frequency of abnormality across 400 CU individuals (100 per tracer). The pooled multitracer ranking was used to create a staging model consisting of 4 clusters of regions because it displayed a high and consistent correlation with each single-tracer ranking. Relationships between amyloid stage, clinical variables, and longitudinal cognitive decline were investigated. <h3>Results</h3> SUVr abnormality was most frequently observed in cingulate, followed by orbitofrontal, precuneal, and insular cortices and then the associative, temporal, and occipital regions. Abnormal amyloid levels based on binary global SUVr classification were observed in 1.0%, 5.5%, 17.9%, 90.0%, and 100.0% of individuals in stage 0 to 4, respectively. Baseline stage predicted decline in Mini-Mental State Examination (MMSE) score (ADNI: n = 867, <i>F</i> = 67.37, <i>p</i> &lt; 0.001; OASIS: n = 475, <i>F</i> = 9.12, <i>p</i> &lt; 0.001) and faster progression toward an MMSE score ≤25 (ADNI: n = 787, hazard ratio [HR]<sub>stage1</sub> 2.00, HR<sub>stage2</sub> 3.53, HR<sub>stage3</sub> 4.55, HR<sub>stage4</sub> 9.91, <i>p</i> &lt; 0.001; OASIS: n = 469, HR<sub>stage4</sub> 4.80, <i>p</i> &lt; 0.001). <h3>Conclusion</h3> The pooled multitracer staging model successfully classified the level of amyloid burden in &gt;3,000 individuals across cohorts and radiotracers and detects preglobal amyloid burden and distinct risk profiles of cognitive decline within globally amyloid-positive individuals.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

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

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 head0.046
GPT teacher head0.345
Teacher spread0.299 · 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 designSimulation or modeling
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

Citations102
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNeurologySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207