The Role of Surgery in IDH-Wild-Type Lower-Grade Gliomas: Threshold at a High Extent of Resection Should be Pursued.

BACKGROUND: While maximizing extent of resection (EOR) is associated with longer survival in lower-grade glioma (LGG) patients, the number of cases remains insufficient in determining a EOR threshold to elucidate the clinical benefits, especially in IDH-wild-type LGG patients. OBJECTIVE: To identify the effects of EOR on the survival outcomes of IDH-wild-type LGG patients. METHODS: IDH-wild-type LGG patients were retrospectively reviewed. The effect of EOR and other predictor variables on overall survival (OS) and progression-free survival (PFS) was analyzed using Cox regression models and the Kaplan-Meier method. RESULTS: A total of 94 patients (median OS: 48.9 mo; median follow-up: 30.6 mo) were included in this study. In the multivariable Cox regression analysis, postoperative residual volume was associated with prolonged OS (HR = 2.238; 95% confidence interval [CI], 1.130-4.435; P = .021) and PFS (HR = 2.075; 95% CI, 1.113-3.869; P = .022). Thresholds at a minimum EOR of 97.0% or a maximum residue of 3.0 cm3 were necessary to impact OS positively. For the telomerase reverse transcriptase (TERT)p-wild-type group, such an association was absent. Significant differences in survival existed between the TERTp-wild-type and mutant patients who underwent relatively incomplete resections (residual ≥2.0 cm3 + TERTp wild type: median OS of 62.6 mo [95% CI: 39.7-85.5 mo]; residual ≥2.0 cm3 + TERTp mutant: median OS of 20.0 mo [95% CI:14.6-25.4 mo]). CONCLUSION: Our results support the core role of maximal safe resection in the treatment of IDH-wild-type LGGs, especially for IDH-wild-type + TERTp-mutant LGGs. Importantly, the survival benefits of surgery could only be elucidated at a high EOR cut-off point.

Differentiation of Treatment-Related Effects from Glioma Recurrence Using Machine Learning Classifiers Based Upon Pre-and Post-Contrast T1WI and T2 FLAIR Subtraction Features: A Two-Center Study.

PURPOSE: We propose three support vector machine (SVM) classifiers, using pre-and post-contrast T2 fluid-attenuated inversion recovery (FLAIR) subtraction and/or pre-and post-contrast T1WI subtraction, to differentiate treatment-related effects (TRE) from glioma recurrence. MATERIALS AND METHODS: Fifty-six postoperative high-grade glioma patients with suspicious progression after radiotherapy and chemotherapy from two centers were studied. Pre-and post-contrast T1WI and T2 FLAIR were collected. Each pre-contrast image was voxel-wise subtracted from the co-registered post-contrast image. Dataset was randomly split into training, and testing on a 7:3 ratio, accordingly subjected to a five fold cross validation. Best feature subsets were selected by Pearson correlation coefficient and recursive feature elimination, whereupon a radiomics classifier was built with SVM. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: In all, 186 features were extracted on each subtraction map. Top nine T1WI subtraction features, top thirteen T2 FLAIR subtraction features and top thirteen combination features were selected to build optimal SVM classifiers accordingly. The accuracies/AUCs/sensitivity/specificity/PPV/NPV of SVM based on sole T1WI subtraction were 80.00%/80.00% (CI: 0.5370-1.0000)/100%/70.00%/62.50%/100%. Those results of SVM based on sole T2 FLAIR subtraction were 86.67%/84.00% (CI: 0.5962-1.0000)/100%/80%/71.43%/100%. Those results of SVM based on both T1WI subtraction and T2 FLAIR subtraction were 93.33%/94.00% (CI: 0.7778-1.0000)/100%/90%/83.33%/100%, respectively. CONCLUSION: Pre- and post-contrast T2 FLAIR subtraction provided added value for diagnosis between recurrence and TRE. SVM based on a combination of T1WI and T2 FLAIR subtraction maps was superior to the sole use of T1WI or T2 FLAIR for differentiating TRE from recurrence. The SVM classifier based on combination of pre-and post-contrast subtraction T2 FLAIR and T1WI imaging allowed for the accurate differential diagnosis of TRE from recurrence, which is of paramount importance for treatment management of postoperative glioma patients after radiation therapy.