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Record W2892155071 · doi:10.1097/rli.0000000000000510

Linearity, Bias, Intrascanner Repeatability, and Interscanner Reproducibility of Quantitative Multidynamic Multiecho Sequence for Rapid Simultaneous Relaxometry at 3 T

2018· article· en· W2892155071 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

VenueInvestigative Radiology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsRepeatabilityReproducibilityImaging phantomRelaxometryVolunteerNuclear medicineLinearityNuclear magnetic resonanceMedicineMagnetic resonance imagingChemistryRadiologyChromatographyPhysicsSpin echo

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study was to evaluate the linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative values derived from a multidynamic multiecho (MDME) sequence for rapid simultaneous relaxometry. MATERIALS AND METHODS: The NIST/ISMRM (National Institute of Standards and Technology/International Society for Magnetic Resonance in Medicine) phantom, containing spheres with standardized T1 and T2 relaxation times and proton density (PD), and 10 healthy volunteers, were scanned 10 times on different days and 2 times during the same session, using the MDME sequence, on three 3 T scanners from different vendors. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. The measured phantom values were compared with reference values; volunteer values were compared with their averages across 3 scanners. RESULTS: The linearity of both phantom and volunteer measurements in T1, T2, and PD values was very strong (R = 0.973-1.000, 0.979-1.000, and 0.982-0.999, respectively) The highest intrascanner coefficients of variation (CVs) for T1, T2, and PD were 2.07%, 7.60%, and 12.86% for phantom data, and 1.33%, 0.89%, and 0.77% for volunteer data, respectively. The highest interscanner CVs of T1, T2, and PD were 10.86%, 15.27%, and 9.95% for phantom data, and 3.15%, 5.76%, and 3.21% for volunteer data, respectively. Variation of T1 and T2 tended to be larger at higher values outside the range of those typically observed in brain tissue. The highest intrascanner and interscanner CVs for brain tissue volumetry were 2.50% and 5.74%, respectively, for cerebrospinal fluid. CONCLUSIONS: Quantitative values derived from the MDME sequence are overall robust for brain relaxometry and volumetry on 3 T scanners from different vendors. Caution is warranted when applying MDME sequence on anatomies with relaxometry values outside the range of those typically observed in brain tissue.

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)0.001
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
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 head0.116
GPT teacher head0.386
Teacher spread0.270 · 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