Difference spectroscopy using PRESS asymmetry: application to glutamate, glutamine, and myo‐inositol
Bibliographic record
Abstract
A simple, clinically viable technique utilizing PRESS and strong coupling properties is presented for discrimination of coupled brain metabolites. The method relies on signal variation due to alteration of inter-echo timings (PRESS asymmetry) while maintaining a constant total echo time. Spin response of singlets and weakly coupled spins is unchanged due to PRESS asymmetry, allowing difference spectroscopy to detect unobstructed strongly coupled resonances. No changes to the standard PRESS sequence are required except variation of inter-echo timings. The procedure is illustrated for the separate detection of glutamate from glutamine and the detection of myo-inositol in simulation, phantom, and in vivo experiments at 4.7 T. The subtraction yields calculated from the simulation were 53% for glutamate and 75% for myo-inositol, and a resultant contribution of 96% glutamate to the total glutamate/glutamine multiplet in the 2.04-2.14 ppm range. To extend the treatment to other field strengths and metabolites, an analytical approximation based on a strongly coupled AB system was used to model individual spin groups. Subtraction spectroscopy yields for different combinations of coupling parameters were calculated for the detection of various strongly coupled metabolites at common clinical field strengths. The approximation also predicts adequate glutamate/glutamine discrimination at 3.0 T using the difference spectroscopy method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".