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Record W2041750706 · doi:10.1002/jmri.21079

Investigating exchange and multicomponent relaxation in fully‐balanced steady‐state free precession imaging

2008· article· en· W2041750706 on OpenAlexafffund
Sean Deoni, Brian K. Rutt, Derek K. Jones

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2008
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsRobarts Clinical Trials
FundersCanadian Institutes of Health Research
KeywordsSteady-state free precession imagingRelaxation (psychology)PrecessionNuclear magnetic resonanceSIGNAL (programming language)T2 relaxationPulse (music)MagnetizationRelaxometryChemistryPhysicsComputational physicsStatistical physicsMagnetic resonance imagingOpticsSpin echoCondensed matter physicsComputer scienceMagnetic fieldQuantum mechanicsRadiology

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the effect of chemical exchange and multicomponent relaxation on the rapid T(2) mapping method, DESPOT2 (driven equilibrium single pulse observation of T(2)) and the steady-state free precession (SSFP) sequence upon which it is based. Although capable of rapid T(2) determination, an assumption implicit of the method is single-component relaxation. In many biological tissues (such as white and gray matter), it is well established that the T(2) decay curve is more accurately described by the summation of more than one relaxation species. MATERIALS AND METHODS: The effects of exchange were first incorporated into the general SSFP magnetization expressions and its effect on the measured SSFP signal investigated using Bloch-McConnell simulations. Corresponding imaging experiments were performed to support the presented theory. RESULTS: Simulations show the measured multicomponent SSFP signal may be expressed as a linear summation of signal from each species under usual imaging conditions where the repetition time is much less than T(2). Imaging experiments performed using dairy cream demonstrate strong agreement with the presented theory. Finally, using a dairy cream model, we demonstrate quantification of multicomponent relaxation from multiangle SSFP data for the first time, showing good agreement with reference spin-echo values. CONCLUSION: SSFP and DESPOT2 may provide a new method for investigating multicomponent systems, such as human brain, and disease processes, such as multiple sclerosis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.501

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)0.0000.000

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 head0.019
GPT teacher head0.297
Teacher spread0.279 · 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 designObservational
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

Citations44
Published2008
Admission routes2
Has abstractyes

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