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Record W2169459006 · doi:10.1177/1352458506070928

Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology

2006· article· en· W2169459006 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMultiple Sclerosis Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMyelinLuxol fast blue stainMultiple sclerosisPathologyRelaxometryMagnetic resonance imagingHistopathologyRemyelinationNuclear magnetic resonanceChemistryMedicineNuclear medicineCentral nervous systemRadiologyPhysicsInternal medicineImmunologySpin echo

Abstract

fetched live from OpenAlex

Various magnetic resonance (MR) techniques are used to study the pathological evolution of demyelinating diseases, such as multiple sclerosis (MS). However, few studies have validated MR derived measurements with histopathology. Here, we determine the correlation of myelin water imaging, an MR measure of myelin content, with quantitative histopathologic measures of myelin density. The multi-component T2 distribution of water was determined from 25 formalin-fixed MS brain samples using a multi-echo T2 relaxation MR experiment. The myelin water fraction (MWF), defined as T2 signal below 30 milliseconds divided by the total signal, was determined for various regions of interest and compared to Luxol fast blue (myelin stain) mean optical density (OD) for each sample. MWF had a strong correlation with myelin stain [mean (range) R2 = 0.67 (0.45-0.92)], validating MWF as a measure of myelin density. This quantitative technique has many practical applications for the in vivo monitoring of demyelination and remyelination in a variety of disorders of myelin.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.142
GPT teacher head0.305
Teacher spread0.163 · 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