Role of postoperative tumor volume in patients with MGMT-unmethylated glioblastoma

Pseudoprogression in GBM versus true progression in patients with glioblastoma: A multiapproach analysis

BACKGROUND AND PURPOSE

To investigate the feasibility of using a multiapproach analysis combining clinical data, diffusion- and perfusion-weighted imaging, and 3D magnetic resonance spectroscopic imaging to distinguish true tumor progression (TP) from pseudoprogression (PSP) in patients with glioblastoma.

MATERIALS AND METHODS

Progression was suspected within 6 months of radiotherapy in 46 of the 180 patients included in the Phase-III SpectroGlio trial (NCT01507506). Choline/creatine (Cho/Cr), choline/N-acetyl aspartate (Cho/NAA) and lactate/N-acetyl aspartate (Lac/NAA) ratios were extracted. Apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were calculated. ADC, relative CBV values and tumor volume (TV) were collected at relapse. Differences between TP and PSP were evaluated using Mann-Whitney tests, and p values were adjusted with Bonferroni correction.

RESULTS

Patients with suspected progression underwent a new MRI scan 1 month after the first one. Of these, 28 were classified as PSP, and 18 as TP. After a median follow-up of 41 months, median overall survival was higher in PSP than in TP (25.2 vs 20.3 months; p = 0.0092). Lac/NAA and Cho/Cr ratios were higher in TP than in PSP (1.2 vs 0.5; p = 0.006; and 3 vs 2.2; p = 0.021). After multivariate regression analysis, TV was the most significant predictor of TP vs PSP, and the only one retained in the model (p = 0.028).

CONCLUSION

Three spectroscopic ratios could be used to differentiate PSP from TP. TV at relapse was the most predictive factor in the multivariate analysis, and overall survival was higher in PSP than in TP.

Implications of Cellular Immaturity in Necrosis and Microvascularization in Glioblastomas IDH-Wild-Type

Necrosis and increased microvascular density in glioblastoma IDH-wild-type are the consequence of both hypoxia and cellular immaturity. Our study aimed to identify the main clinical-imaging and morphogenetic risk factors associated with tumor necrosis and microvascular in the prognosis of patient survival. We performed a retrospective study (10 years) in which we identified 39 cases. We used IDH1, Ki-67 and Nestin immunomarkers, as well as CDKN2A by FISH. The data were analyzed using SPSS Statistics. The clinical characterization identified only age over 50 years as a risk factor (HR = 3.127). The presence of the tumor residue, as well as the absence of any therapeutic element from the trimodal treatment, were predictive factors of mortality (HR = 1.024, respectively HR = 7.460). Cellular immaturity quantified by Nestin was associated with reduced overall survival (p = 0.007). Increased microvascular density was associated with an increased proliferative index (p = 0.009) as well as alterations of the CDKN2A gene (p < 0.001). CDKN2A deletions and cellular immaturity were associated with an increased percentage of necrosis (p < 0.001, respectively, p = 0.017). The main risk factors involved in the unfavorable prognosis are moderate and increased Nestin immunointensity, as well as the association of increased microvascular density with age over 50 years. Necrosis was not a risk factor.

Surgical Treatment of Glioblastoma: State-of-the-Art and Future Trends

Glioblastoma (GBM) is a highly aggressive disease and is associated with poor prognosis despite treatment advances in recent years. Surgical resection of tumor remains the main therapeutic option when approaching these patients, especially when combined with adjuvant radiochemotherapy. In the present study, we conducted a comprehensive literature review on the state-of-the-art and future trends of the surgical treatment of GBM, emphasizing topics that have been the object of recent study.

Is there a limited value of cytoreductive surgery in elderly patients with malignant gliomas?

Background:

Glioblastoma (GB) is well known for being the most aggressive primary cerebral malignancy. The peak incidence is at 60–70 years of age, with over half of patients aged over 65 years at diagnosis.

Methods:

Patients with a confirmed histological diagnosis of GB between January 2009 and June 2016 at a single center were retrospectively identified. The inclusion criteria for the study were age over 65 years at diagnosis, and surgical management with either a burr hole biopsy or craniotomy.

Results:

A total of n = 289 patients underwent surgery for GB, with a median age at diagnosis of 71 years, and of whom 64% were male. Craniotomies were performed in 71%, with burr hole biopsies performed in the remainder (29%). Patient survival differed significantly with treatment modality (P < 0.001), ranging from a median of 382 days in those treated with a combination of craniotomy, radiotherapy (RT), and temozolomide (TZM), to 43 days in those only receiving a burr hole biopsy with no further treatment. On multivariable analysis, treatment with RT + TZM was significantly independently associated with longer patient survival (P < 0.001). Craniotomy was associated with a significant improvement in performance status, compared to burr hole biopsy (P = 0.006). For the subgroup of patients receiving TZM, those with a methylated O⁶-methylguanine-DNA-methyltransferase (MGMT) status had significantly longer overall survival than those with unmethylated MGMT (median: 407 vs. 341 days, P = 0.039).

Conclusion:

Our retrospective data demonstrate that the elderly population with GB benefit from aggressive chemo-RT, regardless of surgical intervention.

Clinical strategies to manage adult glioblastoma patients without MGMT hypermethylation

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Standard therapy for GBM comprises surgical resection, followed by radiotherapy plus concomitant and adjuvant temozolomide (TMZ) therapy. The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) promoter is one of the most essential predictive biomarkers for patients with GBM treated with TMZ. Patients with an unmethylated MGMT promoter (umMGMT), who comprise 60% of patients with GBM, present an even worse prognosis because of TMZ resistance. Radiotherapy with various fractionation, chemotherapy compensating for TMZ, targeted therapy against diverse oncogenic pathways, immunotherapy of vaccine or immune checkpoint inhibitor, and tumor treating fields have been studied in umMGMT GBM patients. However, most efforts have yielded negative results or merely minimal improvements. Therefore, effective patient subgroup selection concerning precision medicine has become the focus. By assigning different treatments to the corresponding patient subgroups, a better curative effect and subsequently prolonged survival can be achieved. In this review, we re-evaluate the value of standard TMZ therapy and summarize the new clinical strategies and attempts to treat patients with umMGMT, which yielded positive and negative results, to provide alternative treatment options and discuss future directions of umMGMT GBM treatment.

Development and Practical Implementation of a Deep Learning-Based Pipeline for Automated Pre- and Postoperative Glioma Segmentation

BACKGROUND AND PURPOSE

Quantitative volumetric segmentation of gliomas has important implications for diagnosis, treatment, and prognosis. We present a deep-learning model that accommodates automated preoperative and postoperative glioma segmentation with a pipeline for clinical implementation. Developed and engineered in concert, the work seeks to accelerate clinical realization of such tools.

MATERIALS AND METHODS

A deep learning model, autoencoder regularization-cascaded anisotropic, was developed, trained, and tested fusing key elements of autoencoder regularization with a cascaded anisotropic convolutional neural network. We constructed a dataset consisting of 437 cases with 40 cases reserved as a held-out test and the remainder split 80:20 for training and validation. We performed data augmentation and hyperparameter optimization and used a mean Dice score to evaluate against baseline models. To facilitate clinical adoption, we developed the model with an end-to-end pipeline including routing, preprocessing, and end-user interaction.

RESULTS

The autoencoder regularization-cascaded anisotropic model achieved median and mean Dice scores of 0.88/0.83 (SD, 0.09), 0.89/0.84 (SD, 0.08), and 0.81/0.72 (SD, 0.1) for whole-tumor, tumor core/resection cavity, and enhancing tumor subregions, respectively, including both preoperative and postoperative follow-up cases. The overall total processing time per case was ∼10 minutes, including data routing (∼1 minute), preprocessing (∼6 minute), segmentation (∼1-2 minute), and postprocessing (∼1 minute). Implementation challenges were discussed.

CONCLUSIONS

We show the feasibility and advantages of building a coordinated model with a clinical pipeline for the rapid and accurate deep learning segmentation of both preoperative and postoperative gliomas. The ability of the model to accommodate cases of postoperative glioma is clinically important for follow-up. An end-to-end approach, such as used here, may lead us toward successful clinical translation of tools for quantitative volume measures for glioma.

Evidence-based recommendations on categories for extent of resection in diffuse glioma

Surgical resection represents the standard of care in diffuse glioma, and more extensive tumour resection appears to be associated with favourable outcome. Up to now, terminology to describe extent of resection has been inconsistently applied across clinical trials which hampers comparative analysis of cohorts between different studies. Based on a comprehensive literature review, we developed evidence-based expert recommendations on categories for extent of resection. Recommendations are formulated for the categories 'biopsy', 'partial resection', 'subtotal resection', 'near total resection', 'complete resection' and 'supramaximal resection'. Definitions rest on reduction of contrast- and non-contrast-enhancing tumour in glioblastoma, and on reduction of T2/FLAIR-hyperintense tumour in gliomas WHO grade 2 or 3. Both relative reduction of tumour volume (in percentage) as a measurement of surgical efficacy and absolute residual tumour volume (in cm³) as a measurement of remaining tumour burden are incorporated into the categories for extent of resection. Class of evidence for the proposed categories ranges from class IIB to IV. Limitations of the suggested categories are discussed. The proposed categories on extent of resection offer a framework to standardize nomenclature based on previous studies, and will need to be evaluated in prospective, molecularly well-defined cohorts. Our categories may eventually help as a stratification factor for future clinical trials.

Prognostic factors in patients with glioblastoma multiforme: focus on the pathologic variants

The aim of this study was to offer predicting factors for survival in adult patients with glioblastoma multiforme. 153 consecutive patients with high-grade glioma (WHO grade IV) were studied in Imam Reza hospital, Kermanshah University of Medical Science, Kermanshah, Iran, between April 2003 and April 2017. All patients treated with surgical resection and standard postoperative radiotherapy (54 Gy). Using the patients' charts and electronic medical records system, the following data were obtained: gender, age, Karnofsky performance status (KPS) score on admission, primary vs. secondary type, extent of surgery, tumor location, tumor size, necrosis size, use of Temozolomide (TMZ), pathology subtype, and immunohistochemistry results. Patients were followed from the time of the surgery until the death occurred. Overall survival (OS) and progression-free survival (PFS) were calculated by the Kaplan-Meier method. Survival time curves for various subgroups were compared by the log-rank test. The impact of the suggested prognostic factors on survival was evaluated by univariate and multivariate analyses. Age, gender, KPS, extent of surgery, tumor location, necrosis size, and reoperation in recurrence had not any statistically significant effect on survival. Univariate analysis revealed a significant impact on outcome for pathology subtype (PFS: P < 0.001, OS: P < 0.001), tumor type (primary vs. secondary) (PFS: P = P < 0.001, OS: P < 0.001), tumor size (PFS: P = 0.044, OS: P = 0.04), TMZ therapy (PFS: P < 0.001, OS: P < 0.001), P53 (PFS: P < 0.001, OS: P < 0.001), and Ki67 (PFS: P < 0.001, OS: P < 0.001). In multivariate analysis, independent favorable prognostic factors for survival were pathology subtype (PFS: P < 0.001, OS: P < 0.001), type (PFS: P < 0.001, OS: 0.012), TMZ (PFS: P < 0.001, OS: P < 0.001), P53 (PFS: P < 0.001, OS: P < 0.001), and Ki67 (PFS: P < 0.001, OS: P < 0.001). The results suggest that pathology subtype, primary vs. secondary type, TMZ therapy, P53, and Ki 63 may play an important role in the survival of patients with glioblastoma multiforme. There is no relationship detected between age, gender, KPS, tumor size and location, necrosis size, extent of surgery, reoperation in recurrence, and patient survival.

A balanced score to predict survival of elderly patients newly diagnosed with glioblastoma

BACKGROUND

Over the past years, several treatment regimens have been recommended for elderly patients with glioblastoma (GBM), ranging from ultrahypofractionated radiotherapy (RT) over monochemotherapy (ChT) to combined radiochemotherapy (RChT). The current guidelines recommend active treatment in elderly patients in cases with a KPS of at least 60%. We established a score for selecting patients with a very poor prognosis from patients with a better prognosis.

METHODS

One hundred eighty one patients ≥65 years old, histologically diagnosed with GBM, were retrospectively evaluated. Clinical characteristics were analysed for their impact on the overall survival (OS). Factors which were significant in univariate analysis (log-rank test, p < 0.05) were included in a multi-variate model (multi-variate Cox regression analysis, MVA). The 9-month OS for the significant factors after MVA (p < 0.05) was included in a prognostic score. Score sums with a median OS of < and > 6 months were summarized as Group A and B, respectively.

RESULTS

Age, KPS, MGMT status, the extent of resection, aphasia after surgery and motor dysfunction after surgery were significantly associated with OS on univariate analysis (p < 0.05). On MVA age (p 0.002), MGMT promotor methylation (p 0.013) and Karnofsky performance status (p 0.005) remained significant and were included in the score. Patients were divided into two groups, group A (median OS of 2.7 months) and group B (median OS of 7.8 months). The score was of prognostic significance, independent of the adjuvant treatment regimen.

CONCLUSIONS

The score distinguishes patients with a poor prognosis from patients with a better prognosis. Its inclusion in future retrospective or prospective trials could help enhance the comparability of results. Before its employment on a routine basis, external validation is recommended.

Volumetric assessment of glioblastoma and its predictive value for survival

BACKGROUND

The objective of this study was to evaluate the morphology of glioblastoma on structural pretreatment magnetic resonance imaging (MRI), defining imaging prognostic factors.

METHOD

We conducted a retrospective analysis of MR images from 114 patients harboring a primary glioblastoma, derived from two neurosurgical departments. Tumor segmentation was carried out in a semi-automated fashion. Tumor compartments comprised contrast-enhancing volume (CEV+), perifocal hyperintensity on fluid-attenuated inversion recovery (FLAIR) images (FLAIR+) excluding CEV+, and a non-enhancing area within the CEV+ lesion (CEV-). Additionally, two ratios were calculated from these volumes, the edema-tumor ratio (ETR) and necrosis-tumor ratio (NTR). All patients received surgical resection, followed by concomitant radiation and chemotherapy.

RESULTS

Tumor segmentation revealed the strongest correlation between the CEV+ volume and the CEV-, presenting intratumoral necrosis (p < 0.001). The relation between the tumor surrounding the FLAIR+ area and the CEV+ volume and the ETR is inversely correlated (p = 0.001). The most important prognostic factor in multivariable analysis was NTR (HR 2.63, p = 0.016). The cut-off value in our cohort for NTR was 0.33, equivalent to a decrease in survival if the necrotic core of the tumor (CEV-) accounts for more than 33% of the tumor mass itself (CEV+).

CONCLUSIONS

Our data emphasizes the importance of the necrosis-tumor ratio as a biomarker in glioblastoma imaging, rather than single tumor compartment volumes. NTR can help to identify a subset of tumors with a higher resistance to therapy and a dismal prognosis.