Extent of Surgical Resection in Lower-Grade Gliomas: Differential Impact Based on Molecular Subtype

Patel, Sohil H.; Bansal, Ashank; Young, Eun; Batchala, Prem P.; Patrie, James T.; Lopes, M. Beatriz; Jain, Rajan; Fadul, Camilo E.; Schiff, David

doi:10.3174/ajnr.a6102

Cited by 74 publications

(51 citation statements)

References 30 publications

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“…57 Similarly, we found that gross total resection did not confer a better prognosis relative to partial resection, as other papers have reported [58][59][60][61] ; one prior paper also reported that gross total resection may only be prognosis in IDH-mutated gliomas. 62 Age, sex, and tumor grade were also not prognostic in our cohort, consistent with prior analyses in LGG cohorts 60,61,63 and that tumor genetics are stronger predictors than histological grade. 10,11 The main limitations of our study were the retrospective single-center design and sample size.…”

Section: Discussionsupporting

confidence: 88%

“…Furthermore, it is possible that adjuvant radiation and chemotherapy may only benefit younger patients 56 or only be evident during much longer follow‐up periods 57 . Similarly, we found that gross total resection did not confer a better prognosis relative to partial resection, as other papers have reported 58‐61 ; one prior paper also reported that gross total resection may only be prognosis in IDH‐mutated gliomas 62 . Age, sex, and tumor grade were also not prognostic in our cohort, consistent with prior analyses in LGG cohorts 60,61,63 and that tumor genetics are stronger predictors than histological grade 10,11 …”

Section: Discussionsupporting

confidence: 74%

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The Prognostic Value of MRI Subventricular Zone Involvement and Tumor Genetics in Lower Grade Gliomas

Chiang

Pisapia

Liechty

et al. 2020

Journal of Neuroimaging

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BACKGROUND AND PURPOSE: Glioblastomas (GBMs) that involve the subventricular zone (SVZ) have a poor prognosis, possibly due to recruitment of neural stem cells. The purpose of this study was to evaluate whether SVZ involvement by lower grade gliomas (LGG), WHO grade II and III, similarly predicts poorer outcomes. We further assessed whether tumor genetics and cellularity are associated with SVZ involvement and outcomes. METHODS: Forty-five consecutive LGG patients with preoperative imaging and next generation sequencing were included in this study. Regional SVZ involvement and whole tumor apparent diffusion coefficient (ADC) values, as a measure of cellularity, were assessed on magnetic resonance imaging. Progression was determined by RANO criteria. Kaplan-Meier curves and Cox regression analyses were used to determine the hazard ratios (HR) for progression and survival. RESULTS: Frontal, parietal, temporal, and overall SVZ involvement and ADC values were not associated with progression or survival (P ≥ .05). However, occipital SVZ involvement, seen in two patients, was associated with a higher risk of tumor progression (HR = 6.6, P = .016) and death (HR = 31.5, P = .015), CDKN2A/B mutations (P = .03), and lower ADC histogram values at the 5th (P = .026) and 10th percentiles (P = .046). Isocitrate dehydrogenase, phosphatase and tensin homolog, epidermal growth factor receptor, and cyclin-dependent kinase 4 mutations were also prognostic (P ≤ .05). CONCLUSIONS: Unlike in GBM, overall SVZ involvement was not found to strongly predict poor prognosis in LGGs. However, occipital SVZ involvement, though uncommon, was prognostic and found to be associated with CDKN2A/B mutations and tumor hypercellularity. Further investigation into these molecular mechanisms underlying occipital SVZ involvement in larger cohorts is warranted.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 74%

The Prognostic Value of MRI Subventricular Zone Involvement and Tumor Genetics in Lower Grade Gliomas

Chiang

Pisapia

Liechty

et al. 2020

Journal of Neuroimaging

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“…The extent of surgical resection in particular is well-recognized for its impact on the overall survival of a patient with LGG. 46,47 Nonetheless, our study has limitations. This is a retrospective study and thus inherently limited by design in its ability to infer relationships beyond association.…”

Section: Discussionmentioning

confidence: 87%

Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes

Darvishi¹,

Batchala²,

Patrie³

et al. 2020

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE: Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories. MATERIALS AND METHODS:We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status.

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“…It should be noted that IDH mutation status has been integrated into the 2016 WHO Classification of Tumors of the Central Nervous System, Revised 4th edition ( 1 ). Furthermore, it has been reported that due to different molecular subtypes, the choice of surgical resection range has different survival effects on patients with lower-grade glioma (grades II and III) ( 6 ). Based on the above research ( 5 – 7 ), it is necessary to predict the IDH status accurately before surgery and to guide the clinical development of appropriate tumor treatment plans.…”

Section: Introductionmentioning

confidence: 99%

Predictive Role of the Apparent Diffusion Coefficient and MRI Morphologic Features on IDH Status in Patients With Diffuse Glioma: A Retrospective Cross-Sectional Study

et al. 2021

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PurposeTo evaluate isocitrate dehydrogenase (IDH) status in clinically diagnosed grade II~IV glioma patients using the 2016 World Health Organization (WHO) classification based on MRI parameters.Materials and MethodsOne hundred and seventy-six patients with confirmed WHO grade II~IV glioma were retrospectively investigated as the study set, including lower-grade glioma (WHO grade II, n = 64; WHO grade III, n = 38) and glioblastoma (WHO grade IV, n = 74). The minimum apparent diffusion coefficient (ADCmin) in the tumor and the contralateral normal-appearing white matter (ADCn) and the rADC (ADCmin to ADCn ratio) were defined and calculated. Intraclass correlation coefficient (ICC) analysis was carried out to evaluate interobserver and intraobserver agreement for the ADC measurements. Interobserver agreement for the morphologic categories was evaluated by Cohen’s kappa analysis. The nonparametric Kruskal-Wallis test was used to determine whether the ADC measurements and glioma subtypes were related. By univariable analysis, if the differences in a variable were significant (P<0.05) or an image feature had high consistency (ICC >0.8; κ >0.6), then it was chosen as a predictor variable. The performance of the area under the receiver operating characteristic curve (AUC) was evaluated using several machine learning models, including logistic regression, support vector machine, Naive Bayes and Ensemble. Five evaluation indicators were adopted to compare the models. The optimal model was developed as the final model to predict IDH status in 40 patients with glioma as the subsequent test set. DeLong analysis was used to compare significant differences in the AUCs.ResultsIn the study set, six measured variables (rADC, age, enhancement, calcification, hemorrhage, and cystic change) were selected for the machine learning model. Logistic regression had better performance than other models. Two predictive models, model 1 (including all predictor variables) and model 2 (excluding calcification), correctly classified IDH status with an AUC of 0.897 and 0.890, respectively. The test set performed equally well in prediction, indicating the effectiveness of the trained classifier. The subgroup analysis revealed that the model predicted IDH status of LGG and GBM with accuracy of 84.3% (AUC = 0.873) and 85.1% (AUC = 0.862) in the study set, and with the accuracy of 70.0% (AUC = 0.762) and 70.0% (AUC = 0.833) in the test set, respectively.ConclusionThrough the use of machine-learning algorithms, the accurate prediction of IDH-mutant versus IDH-wildtype was achieved for adult diffuse gliomas via noninvasive MR imaging characteristics, including ADC values and tumor morphologic features, which are considered widely available in most clinical workstations.

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Extent of Surgical Resection in Lower-Grade Gliomas: Differential Impact Based on Molecular Subtype

Cited by 74 publications

References 30 publications

The Prognostic Value of MRI Subventricular Zone Involvement and Tumor Genetics in Lower Grade Gliomas

The Prognostic Value of MRI Subventricular Zone Involvement and Tumor Genetics in Lower Grade Gliomas

Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes

Predictive Role of the Apparent Diffusion Coefficient and MRI Morphologic Features on IDH Status in Patients With Diffuse Glioma: A Retrospective Cross-Sectional Study

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