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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».