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Record W2556885652 · doi:10.1109/nssmic.2006.356432

Kinetic Modeling of FDG uptake in rat tumors During photodynamic therapy

2006· article· en· W2556885652 on OpenAlexaff
M’hamed Bentourkia, Véronique Bérard, Paté Boubacar, Johan E. van Lier, Roger Lecomte

Bibliographic record

Venue2006 IEEE Nuclear Science Symposium Conference Record · 2006
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhotodynamic therapyFluorodeoxyglucoseNuclear medicineMedicinePhotosensitizerBlood supplyPositron emission tomographyCancerAdenocarcinomaChemistryInternal medicineSurgeryPhotochemistry

Abstract

fetched live from OpenAlex

The aim of this work was to assess by kinetic modeling the effects of the photodynamic therapy (PDT) of cancer in two mammary adenocarcinoma tumors implanted in the axillary areas of rats. One tumor served as control while the other was treated with red light 24 hours after administration of two types of photosensitizers: AlPcS4 (n = 4) and ZnPcS2 (n = 4). PET scans were carried on, with a continuous infusion of fluorodeoxyglucose (FDG), during 2 hours including the 30 min duration of the illumination. The usual FDG kinetic model was modified to include the effects of the treatment. Since the blood supply to the tumors was affected by the illumination during the PET scans, the input curve was derived from factor analysis. A study of the model compartments and rate constants is presented for both AlPcS4 and ZnPcS2.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 designBench or experimental
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

Citations1
Published2006
Admission routes1
Has abstractyes

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