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Record W4320499385 · doi:10.1002/trc2.12372

Development, initial validation, and application of a visual read method for [ <sup>18</sup> F]MK‐6240 tau PET

2023· article· en· W4320499385 on OpenAlexaff
Joanna L. Shuping, Dawn C. Matthews, Katarzyna Adamczuk, David Scott, Christopher C. Rowe, William Charles Kreisl, Sterling C. Johnson, Ana Lukić, Keith A. Johnson, Pedro Rosa‐Neto, Randolph D. Andrews, Koen Van Laere, Lindsay Cordes, Larry D. Ward, Claire L. Wilde, Jerome Barakos, Derk D. Purcell, Davangere P. Devanand, Yaakov Stern, José A. Luchsinger, Cyrille Sur, Julie C. Price, Adam M. Brickman, William E. Klunk, Adam L. Boxer, Sulantha Mathotaarachchi, Patrick J. Lao, Jeffrey L. Evelhoch

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityPediatric Oncology Group
FundersNational Institute on AgingMedical Center, University of PittsburghCerveau TechnologiesMassachusetts General HospitalBiogenUniversity of Pittsburgh
KeywordsConcordanceGold standard (test)Positron emission tomographyNuclear medicinePsychologyTemporal lobeNeuroimagingCognitive impairmentMedicineNeuroscienceCognitionRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The positron emission tomography (PET) radiotracer [ 18 F]MK‐6240 exhibits high specificity for neurofibrillary tangles (NFTs) of tau protein in Alzheimer's disease (AD), high sensitivity to medial temporal and neocortical NFTs, and low within‐brain background. Objectives were to develop and validate a reproducible, clinically relevant visual read method supporting [ 18 F]MK‐6240 use to identify and stage AD subjects versus non‐AD and controls. Methods Five expert readers used their own methods to assess 30 scans of mixed diagnosis (47% cognitively normal, 23% mild cognitive impairment, 20% AD, 10% traumatic brain injury) and provided input regarding regional and global positivity, features influencing assessment, confidence, practicality, and clinical relevance. Inter‐reader agreement and concordance with quantitative values were evaluated to confirm that regions could be read reliably. Guided by input regarding clinical applicability and practicality, read classifications were defined. The readers read the scans using the new classifications, establishing by majority agreement a gold standard read for those scans. Two naïve readers were trained and read the 30‐scan set, providing initial validation. Inter‐rater agreement was further tested by two trained independent readers in 131 scans. One of these readers used the same method to read a full, diverse database of 1842 scans; relationships between read classification, clinical diagnosis, and amyloid status as available were assessed. Results Four visual read classifications were determined: no uptake, medial temporal lobe (MTL) only, MTL and neocortical uptake, and uptake outside MTL. Inter‐rater kappas were 1.0 for the naïve readers gold standard scans read and 0.98 for the independent readers 131‐scan read. All scans in the full database could be classified; classification frequencies were concordant with NFT histopathology literature. Discussion This four‐class [ 18 F]MK‐6240 visual read method captures the presence of medial temporal signal, neocortical expansion associated with disease progression, and atypical distributions that may reflect different phenotypes. The method demonstrates excellent trainability, reproducibility, and clinical relevance supporting clinical use. Highlights A visual read method has been developed for [ 18 F]MK‐6240 tau positron emission tomography. The method is readily trainable and reproducible, with inter‐rater kappas of 0.98. The read method has been applied to a diverse set of 1842 [ 18 F]MK‐6240 scans. All scans from a spectrum of disease states and acquisitions could be classified. Read classifications are consistent with histopathological neurofibrillary tangle staging literature.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.342
GPT teacher head0.588
Teacher spread0.246 · 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.

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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Citations26
Published2023
Admission routes1
Has abstractyes

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