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Measuring the Integrity of the Human Blood–Brain Barrier Using Magnetic Resonance Imaging

2010· article· en· W127714186 on OpenAlexaff
Andrea Kassner, Rebecca E. Thornhill

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMagnetic resonance imagingBlood–brain barrierDynamic contrast-enhanced MRIMedicineContrast (vision)RadiologyComputer scienceCentral nervous systemInternal medicine

Abstract

fetched live from OpenAlex

The evaluation of blood-brain barrier (BBB) integrity with contrast-enhanced magnetic resonance imaging (MRI) may prove valuable in the setting of certain brain pathologies, such as brain tumors and acute ischemic stroke. Various MRI protocols have been developed to explore the integrity of the BBB by monitoring the leakage of intravenously administered contrast medium into the brain parenchyma. In its simplest form, BBB integrity is assessed qualitatively, by determining the presence or absence of contrast-enhancement on a structural MR image. When a dynamic contrast-enhanced (DCE) MRI protocol is combined with a suitable pharmacokinetic model, DCE-MRI can map the spatial distribution of BBB integrity throughout the brain and assist with evaluating the effects of therapy. Several model-free surrogate measures of BBB permeability have been recently proposed, all of which can be readily computed from standard dynamic susceptibility contrast MRI perfusion scans. Contrast-enhanced MRI offers multiple strategies for evaluating BBB integrity.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.562
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.415
Teacher spread0.365 · 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 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

Citations33
Published2010
Admission routes1
Has abstractyes

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