MO‐G‐18C‐07: Improving T2 Determination and Quantification of Lipid Methylene Protons in Proton Magnetic Resonance Spectroscopy at 3 T
Bibliographic record
Abstract
Purpose: To improve proton magnetic resonance spectroscopy (MRS) transverse relaxation (T2) determination and quantification of lipid methylene chain (1.3 ppm) protons by rewinding their J‐coupling evolution. Methods: MRS experiments were performed on four lipid phantoms, namely, almond, corn, sunflower and oleic acid, using a 3 T Philips MRI scanner with a transmit/receive birdcage head coil. Two PRESS (Point RESolved Spectroscopy) pulse sequences were used. The first PRESS sequence employed standard bandwidth (BW) (∼550 Hz) RF (radiofrequency) refocussing pulses, while the second used refocussing pulses of narrow BW (∼50 Hz) designed to rewind J‐coupling evolution of the methylene protons in the voxel of interest. Signal was acquired with each sequence from a 5×5×5 mm3 voxel, with a repetition time (TR) of 3000 ms, and with echo times (TE) of 100 to 200 ms in steps of 20 ms. 2048 sample points were measured with a 2000 Hz sampling bandwidth. Additionally, 30 mm outer volume suppression slabs were used to suppress signal outside the voxel of interest. The frequency of the RF pulses was set to that of the methylene resonance. Methylene peak areas were calculated and fitted in MATLAB to a monexponentially decaying function of the form M0exp(‐TE/T2), where M0 is the extrapolated area when TE = 0 ms and yields a measure of concentration. Results: The determined values of M0 and T2 increased for all fatty acids when using the PRESS sequence with narrow BW refocussing pulses. M0 and T2 values increased by an average amount (over all the phantoms) of 31% and 14%, respectively. Conclusion: This investigation has demonstrated that J‐coupling interactions of lipid methylene protons causes non‐negligible signal losses which, if not accounted for, Result in underestimations of their levels and T2 values when performing MRS measurements. Funded by the Natural Sciences and Engineering Research Council of Canada and the Canadian Breast Cancer Foundation – Prairies.NWT
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".