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Simultaneous MRI measurement of blood flow, blood volume, and capillary permeability in mammary tumors using two different contrast agents

2000· article· en· W2049171359 on OpenAlexaff
Elizabeth Henderson, Dick Drost, Hanns‐Joachim Weinmann, Brian K. Rutt, Ting‐Yim Lee

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2000
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsRobarts Clinical TrialsWestern UniversitySt Joseph's Health CareLondon Health Sciences CentreLawson Health Research Institute
Fundersnot available
KeywordsMagnetic resonance imagingBlood flowVascular permeabilityCapillary actionPermeability (electromagnetism)GadoliniumNuclear magnetic resonanceNuclear medicineGadolinium DTPAContrast (vision)Blood volumeDynamic contrastChemistryBiomedical engineeringMaterials sciencePathologyMedicineRadiologyPhysicsInternal medicine

Abstract

fetched live from OpenAlex

A technique for the simultaneous measurement of three vascular parameters: blood flow (Frho), blood volume (v(b)), and the capillary permeability-surface area product (PSrho) in breast tumors using dynamic contrast-enhanced magnetic resonance imaging (MRI) is presented. Features of the technique include measurement of precontrast tumor T(1), rapid temporal sampling, measurement of the arterial input function, and use of a distributed parameter tracer kinetic model. Parameter measurements are compared that were determined using two contrast agents of different molecular weights, gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA; 0.6 kDa) and Gadomer-17 (17 kDa), in 18 spontaneous canine mammary tumors. Measurements of Frho and v(b) corresponded well with literature values, and the mean PSrho measured using Gd-DTPA was a factor of 15 higher than that measured using Gadomer-17. J. Magn. Reson. Imaging 2000;12:991-1003.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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 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

Citations140
Published2000
Admission routes1
Has abstractyes

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