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Record W4289518343 · doi:10.1002/nbm.4808

Inhomogeneous magnetization transfer imaging: Concepts and directions for further development

2022· review· en· W4289518343 on OpenAlexaff
David C. Alsop, Ece Ercan, Olivier M. Girard, Alex L. MacKay, Carl A. Michal, Gopal Varma, Elena Vinogradov, Guillaume Duhamel

Bibliographic record

VenueNMR in Biomedicine · 2022
Typereview
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeAgence Nationale de la Recherche
KeywordsMagnetization transferMagnetizationRelaxation (psychology)Nuclear magnetic resonanceSpinsDipoleProtonPhysicsSIGNAL (programming language)Materials scienceCondensed matter physicsMagnetic fieldChemical physicsMagnetic resonance imagingComputer scienceNeuroscienceNuclear physicsBiology

Abstract

fetched live from OpenAlex

Off‐resonance radio frequency irradiation can induce the ordering of proton spins in the dipolar fields of their neighbors, in molecules with restricted mobility. This dipolar order decays with a characteristic relaxation time, T 1D , that is very different from the T 1 and T 2 relaxation of the nuclear alignment with the main magnetic field. Inhomogeneous magnetization transfer (ihMT) imaging is a refinement of magnetization transfer (MT) imaging that isolates the MT signal dependence on dipolar order relaxation times within motion‐constrained molecules. Because T 1D relaxation is a unique contrast mechanism, ihMT may enable improved characterization of tissue. Initial work has stressed the high correlation between ihMT signal and myelin density. Dipolar order relaxation appears to be much longer in membrane lipids than other molecules. Recent work has shown, however, that ihMT acquisitions may also be adjusted to emphasize different ranges of T 1D . These newer approaches may be sensitive to other microstructural components of tissue. Here, we review the concepts and history of ihMT and outline the requirements for further development to realize its full potential.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.038
GPT teacher head0.360
Teacher spread0.322 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations27
Published2022
Admission routes1
Has abstractyes

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