Diagnostic Accuracy of <scp><sup>1</sup>H</scp>‐<scp>MRS</scp> Using <scp>PRESS</scp> and <scp>MEGA</scp>‐<scp>PRESS</scp> Techniques in the Preoperative Grading of Patients With Gliomas
Bibliographic record
Abstract
BACKGROUND: Edited MRS technique such as MEshcher-GArwood Point RESolved Spectroscopy (MEGA-PRESS) can determine isocitrate dehydrogenase mutation (IDH) mutation status in patients with gliomas but its accuracy in assessing glioma grade has not yet been formally evaluated. PURPOSE: To evaluate the diagnostic accuracy of metabolites such as lactate obtained from the PRESS and MEGA-PRESS sequences in the preoperative grading of glioma. To assess the prognostic value of those metabolite ratios in the overall survival of patients with gliomas. STUDY TYPE: Prospective. SUBJECTS: Sixty-nine subjects with gliomas (16 grade 2, 21 grade 3, and 32 grade 4). Mean age was 50.5 ± 16.7 years; 38 were male and 31 were female. FIELD STRENGTH/SEQUENCE: 3 T/MEGA-PRESS, PRESS. ASSESSMENT: Single voxel PRESS and MEGA-PRESS spectra were obtained from tumors in patients undergoing preoperative MRI. Several tumor metabolites were measured from the PRESS, MEGA-PRESS edit-off, and difference spectra using LCModel (Linear Combination of Model Spectra) software. Diagnosis and glioma grading was done using the World Health Organization (WHO) 2016 classification. Overall survival was assessed. STATISTICAL TESTS: Diagnostic accuracy was measured using receiver-operating characteristic (ROC) curve. Univariate and multivariate Cox proportional hazards modeling was used for the assessment of prognostic factors for time to death. RESULTS: In the differentiation between low- vs. high-grade gliomas, tCr/tCho ratios obtained from PRESS and MEGA-PRESS sequences had similar accuracies (area under the ROC curves [AUCs] = 0.71) while Lac/NAA from PRESS had a lower accuracy (AUC = 0.65). The presence of a detectable 2-hydroxyglutarate peak on the difference spectrum was a favorable prognostic factor in univariate analysis (hazard ratio = 0.25, 95% confidence interval: 0.08-0.83). No other metabolite was found to be a significant prognostic factor in univariate and multivariate analyses. DATA CONCLUSION: Edited MRS can be used to detect metabolites which can help in the preoperative grading of gliomas and in determination of the overall survival. A separate PRESS acquisition is needed for lactate quantification. PLAIN LANGUAGE SUMMARY: Gliomas are brain tumors that vary in severity. This study explored the use of two advanced MR spectroscopy techniques (PRESS and MEGA-PRESS) in detecting tumor metabolites. The authors found that both techniques' choline/creatine ratio showed moderate accuracy in identifying high-grade gliomas. Lactate was better revealed with the PRESS technique and was associated with high-grade gliomas. They confirmed that the MEGA-PRESS technique allowed additional detection of 2-hydroxyglutarate in IDH-mutant gliomas, which was linked to better survival. These findings emphasize that advanced MR spectroscopy can extract metabolic information time-efficiently, which can be used to improve the preoperative diagnosis of patients with gliomas. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".