A rapid inversion technique for the measurement of longitudinal relaxation times of brain metabolites: application to lactate in high‐grade gliomas at 3 T
Bibliographic record
Abstract
The aim of this study was to develop a time-efficient inversion technique to measure the T1 relaxation time of the methyl group of lactate (Lac) in the presence of contaminating lipids and to measure T1 at 3 T in a cohort of primary high-grade gliomas. Three numerically optimized inversion times (TIs) were chosen to minimize the expected error in T1 estimates for a given input total scan duration (set to be 30 min). A two-cycle spectral editing scheme was used to suppress contaminating lipids. The T1 values were then estimated from least-squares fitting of signal measurements versus TI. Lac T1 was estimated as 2000 ± 280 ms. After correcting for T1 (and T2 from literature values), the mean absolute Lac concentration was estimated as 4.3 ± 2.6 mm. The technique developed agrees with the results obtained by standard inversion recovery and can be used to provide rapid T1 estimates of other spectral components as required. Lac T1 exhibits similar variations to other major metabolites observable by MRS in high-grade gliomas. The T1 estimate provided here will be useful for future MRS studies wishing to report relaxation-corrected estimates of Lac concentration as an objective tumor biomarker. Copyright © 2016 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".