Design of cosine modulated very selective suppression pulses for MR spectroscopic imaging at 3T
Bibliographic record
Abstract
The advantages of using a 3 Tesla (T) scanner for MR spectroscopic imaging (MRSI) of brain tissue include improved spectral resolution and increased sensitivity. Very selective saturation (VSS) pulses are important for maximizing selectivity for PRESS MRSI and minimizing chemical shift misregistration by saturating signals from outside the selected region. Although three-dimensional (3D) PRESS MRSI is able to provide excellent quality metabolic data for patients with brain tumors and has been shown to be important for defining tumor burden, the method is currently limited by how much of the anatomic lesion can be covered within a single examination. In this study we designed and implemented cosine modulated VSS pulses that were optimized for 3T MRSI acquisitions. This provided improved coverage and suppression of unwanted lipid signals with a smaller number of pulses. The use of the improved pulse sequence was validated in volunteer studies, and in clinical 3D MRSI exams of brain tumors.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".