Low-Grade Glioma: Correlation of Short Echo Time<sup>1</sup>H-MR Spectroscopy with<sup>23</sup>Na MR Imaging
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: There is considerable variability in the clinical behavior and treatment response of low-grade (WHO grade II) gliomas. The purpose of this work was to characterize the metabolic profile of low-grade gliomas by using short echo time (1)H-MR spectroscopy and to correlate metabolite levels with MR imaging-measured sodium ((23)Na) signal intensity. Based on previous studies, we hypothesized decreased N-acetylaspartate (NAA) and increased myo-inositol (mIns), choline (Cho), glutamate (Glu), and (23)Na signal intensity in glioma tissue. MATERIALS AND METHODS: Institutional ethics committee approval and informed consent were obtained for all of the subjects. Proton ((1)H-MR) spectroscopy (TR/TE = 2200/46 ms) and sodium ((23)Na) MR imaging were performed at 4T in 13 subjects (6 women and 7 men; mean age, 44 years) with suspected low-grade glioma. Absolute metabolite levels were quantified, and relative (23)Na levels were measured in low-grade glioma and compared with the contralateral side in the same patients. Two-sided Student t tests were used to test for statistical significance. RESULTS: Significant decreases were observed for NAA (P < .001) and Glu (P = .004), and increases were observed for mIns (P = .003), Cho (P = .025), and sodium signal intensity (P < .001) in low-grade glioma tissue. Significant correlations (r(2) > 0.25) were observed between NAA and Glu (P < .05) and between NAA and mIns (P < .01). Significant correlations were also observed between (23)Na signal intensity and NAA (P < .01) and between (23)Na signal intensity and Glu (P < .01). Ratios of NAA/mIns, NAA/(23)Na, and NAA/Cho were altered in glioma tissue (P < .001); however based on the t statistic, NAA/(23)Na (t = 9.6) was the most significant, followed by NAA/mIns (t = 6.1), and NAA/Cho (t = 5.0). CONCLUSION: Although Glu concentration is reduced and mIns concentration is elevated in low-grade glioma tissue, the NAA/(23)Na ratio was the most sensitive indicator of pathologic tissue.
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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 | 0.000 | 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 | 0.000 | 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".