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Record W2550149646 · doi:10.1002/mrm.26551

Rapid myelin water imaging in human cervical spinal cord

2016· article· en· W2550149646 on OpenAlexaff
Emil Ljungberg, Irene M. Vavasour, Roger Tam, Youngjin Yoo, Alexander Rauscher, David K.B. Li, Anthony Traboulsee, Alex L. MacKay, Shannon Kolind

Bibliographic record

VenueMagnetic Resonance in Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpinal cordMagnetic resonance imagingMyelinMultiple sclerosisSpin echoT2 relaxationMedicineNuclear medicineWhite matterNuclear magnetic resonanceCentral nervous systemBiomedical engineeringRadiologyPhysicsInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: relaxation is a quantitative MRI technique that can be used as an in vivo biomarker for myelin in the central nervous system. MWI using a multi-echo spin echo sequence currently takes more than 20 min to acquire eight axial slices (5 mm thickness) in the cervical spinal cord, making spinal cord MWI impractical for implementation in clinical studies. METHODS: In this study, an accelerated gradient and spin echo sequence (GRASE), previously validated for brain MWI, was adapted for spinal cord MWI. Ten healthy volunteers were scanned with the GRASE sequence (acquisition time 8.5 min) and compared with the multi-echo spin echo sequence (acquisition time 23.5 min). RESULTS: Using region of interest analysis, myelin estimates obtained from the two sequences were found to be in good agreement (mean difference = -0.0092, 95% confidence interval = - 0.0092 ± 0.061; regression slope = 1.01, ρ = 0.9). MWI using GRASE was shown to be highly reproducible with an average coefficient of variation of 6.1%. CONCLUSION: The results from this study show that MWI can be performed in the cervical spinal cord in less than 10 min, allowing for practical implementation in multimodal clinical studies. Magn Reson Med 78:1482-1487, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.999

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.346
Teacher spread0.319 · 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 designOther design
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

Citations31
Published2016
Admission routes1
Has abstractyes

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