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Record W2783800543 · doi:10.1002/nbm.3868

Can <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratio be used as a myelin‐specific measure in subcortical structures? Comparisons between FSE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios, GRASE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios and multi‐echo GRASE‐based myelin water fractions

2018· article· en· W2783800543 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNMR in Biomedicine · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of ManitobaManitoba HealthHealth Sciences Centre
FundersCanadian Institutes of Health Research
KeywordsWhite matterNuclear medicineNuclear magnetic resonanceLinear regressionMagnetic resonance imagingPhysicsMathematicsMedicineStatisticsRadiology

Abstract

fetched live from OpenAlex

Given the growing popularity of T 1 ‐weighted/ T 2 ‐weighted ( T 1 w/ T 2 w) ratio measurements, the objective of the current study was to evaluate the concordance between T 1 w/ T 2 w ratios obtained using conventional fast spin echo (FSE) versus combined gradient and spin echo (GRASE) sequences for T 2 w image acquisition, and to compare the resulting T 1 w/ T 2 w ratios with histologically validated myelin water fraction (MWF) measurements in several subcortical brain structures. In order to compare these measurements across a relatively wide range of myelin concentrations, whole‐brain T 1 w magnetization prepared rapid acquisition gradient echo (MPRAGE), T 2 w FSE and three‐dimensional multi‐echo GRASE data were acquired from 10 participants with multiple sclerosis at 3 T. Then, after high‐dimensional, non‐linear warping, region of interest (ROI) analyses were performed to compare T 1 w/ T 2 w ratios and MWF estimates (across participants and brain regions) in 11 bilateral white matter (WM) and four bilateral subcortical grey matter (SGM) structures extracted from the JHU_MNI_SS ‘Eve’ atlas. Although the GRASE sequence systematically underestimated T 1 w/ T 2 w values compared to the FSE sequence (revealed by Bland–Altman and mountain plots), linear regressions across participants and ROIs revealed consistently high correlations between the two methods ( r 2 = 0.62 for all ROIs, r 2 = 0.62 for WM structures and r 2 = 0.73 for SGM structures). However, correlations between either FSE‐based or GRASE‐based T 1 w/ T 2 w ratios and MWFs were extremely low in WM structures (FSE‐based, r 2 = 0.000020; GRASE‐based, r 2 = 0.0014), low across all ROIs (FSE‐based, r 2 = 0.053; GRASE‐based, r 2 = 0.029) and moderate in SGM structures (FSE‐based, r 2 = 0.20; GRASE‐based, r 2 = 0.17). Overall, our findings indicated a high degree of correlation (but not equivalence) between FSE‐based and GRASE‐based T 1 w/ T 2 w ratios, and low correlations between T 1 w/ T 2 w ratios and MWFs. This suggests that the two T 1 w/ T 2 w ratio approaches measure similar facets of subcortical tissue microstructure, whereas T 1 w/ T 2 w ratios and MWFs appear to be sensitized to different microstructural properties. On this basis, we conclude that multi‐echo GRASE sequences can be used in future studies to efficiently elucidate both general ( T 1 w/ T 2 w ratio) and myelin‐specific (MWF) tissue characteristics.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
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 score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0070.010
Science and technology studies0.0030.006
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0000.001

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 head0.062
GPT teacher head0.328
Teacher spread0.266 · 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