Estimating relative diglyceride to triglyceride content with localized MRS at 3 T
Bibliographic record
Abstract
It has been previously shown that the MRS sequence stimulated echo acquisition mode (STEAM; mixing time, TM = 20 ms) with an echo time (TE) of 100 ms resolves triglyceride glycerol resonances from that of water at 3 T. The purpose of this work is to determine if STEAM with a TE of 100 ms facilitates relative quantification of diglyceride/triglyceride levels at 3 T. Spectra were obtained from tricaprylin (triglyceride) and dicaprylin (diglyceride) with a range of STEAM TE values (TM = 20 ms). TE values that resulted in two resolved glycerol resonances for triglycerides (rendering them suitable for distinguishing triglyceride contributions from those of diglycerides) were selected. One resonance resides in the 3.85–4.2 ppm spectral range (overlapping the 1,3‐diglyceride resonance) and the other in the 4.2–4.6 ppm spectral range (overlapping one of the 1,2‐diglyceride resonances). STEAM with TE values of 40 ms and 100 ms (TM = 20 ms) yielded two resolvable triglyceride resonances (tricaprylin phantom), at about 4 ppm and 4.4 ppm. Direct integration of the resonances showed that the former peak has 0.86 and 0.17 times the area of the latter for TE = 40 ms and 100 ms, respectively. Spectra obtained from the phantoms containing mixtures of diglyceride (1,3‐dicaprylin) and triglyceride (tricaprylin) were acquired. The triglyceride contribution to the 4 ppm glycerol resonance, a mixture of signal from 1,3‐diglyceride and triglyceride, can be approximated from the area of the 4.4 ppm peak, resulting in an estimate of the 1,3‐diglyceride contribution. Analysis was performed for STEAM TE = 40 ms and TE = 100 ms spectra acquired from phantoms with 1,3‐dicaprylin/tricaprylin weight/weight contents of 2.5%/97.5%, 5%/95%, 10%/90% and 20%/80%. Concentration ratios of 1,3‐dicaprylin/tricaprylin estimated with both STEAM TE values resulted in linear correlations with expected concentration ratios (R2 > 0.99).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".