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Record W4206771328 · doi:10.1097/rlu.0000000000004021

177Lu-FAPI Therapy in a Patient With End-Stage Metastatic Pancreatic Adenocarcinoma

2022· article· en· W4206771328 on OpenAlexaff
Fatemeh Kaghazchi, Ramin Akbarian Aghdam, Shirin Haghighi, Reza Vali, Zohreh Adinehpour

Bibliographic record

VenueClinical Nuclear Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMalignancyNuclear medicineAdenocarcinomaRadiologyWashoutStage (stratigraphy)PathologyCancerInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT: A 52-year-old woman with metastatic pancreatic adenocarcinoma underwent imaging with 18F-FDG PET/CT and 68Ga-FAPI-46 PET/CT, which demonstrated malignancy recurrence in the surgical bed with multiple metastatic lesions, more extensive on 68Ga-FAPI-46 PET/CT. The patient was a candidate for therapy with 177Lu-FAPI-46 due to high uptake of lesions in 68Ga-FAPI-46 images and no other available therapeutic option. Posttreatment 177Lu-FAPI-46 scans showed rather rapid washout of the radiopharmaceutical from tumoral lesions. This case report suggests that, although 68Ga-FAPI-46 is a promising agent for tumor imaging, 177Lu-FAPI-46 may not be an optimal compound for theranostic applications.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0030.002
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 head0.062
GPT teacher head0.346
Teacher spread0.284 · 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 designCase report
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

Citations40
Published2022
Admission routes1
Has abstractyes

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