A change in the apparent diffusion coefficient after treatment with bevacizumab is associated with decreased survival in patients with recurrent glioblastoma multiforme

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning

PURPOSE

The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones.

METHODS

Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature.

RESULTS

Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines.

CONCLUSIONS

Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

The effect of a human vascular endothelial growth factor antibody on the vasculature of human tumor grown in rat brain was studied. Using dynamic contrast-enhanced magnetic resonance imaging, the effects of intravenous bevacizumab (Avastin; 10 mg/kg) were examined before and at postadministration times of 1, 2, 4, 8, 12 and 24 h (N = 26; 4-5 per time point) in a rat model of orthotopic, U251 glioblastoma (GBM). The commonly estimated vascular parameters for an MR contrast agent were: (i) plasma distribution volume (v_p ), (ii) forward volumetric transfer constant (K^trans ) and (iii) reverse transfer constant (k_ep ). In addition, extracellular distribution volume (V_D ) was estimated in the tumor (V_D-tumor ), tumor edge (V_D-edge ) and the mostly normal tumor periphery (V_D-peri ), along with tumor blood flow (TBF), peri-tumoral hydraulic conductivity (K) and interstitial flow (Flux) and tumor interstitial fluid pressure (TIFP). Studied as % changes from baseline, the 2-h post-treatment time point began showing significant decreases in v_p , V_D-tumor, V_D-edge and V_D-peri , as well as K, with these changes persisting at 4 and 8 h in v_p , K, V_{D-tumor, -edge} and _-peri (t-tests; p < 0.05-0.01). Decreases in K^trans were observed at the 2- and 4-h time points (p < 0.05), while interstitial volume fraction (v_e ; = K^trans /k_ep ) showed a significant decrease only at the 2-h time point (p < 0.05). Sustained decreases in Flux were observed from 2 to 24 h (p < 0.01) while TBF and TIFP showed delayed responses, increases in the former at 12 and 24 h and a decrease in the latter only at 12 h. These imaging biomarkers of tumor vascular kinetics describe the short-term temporal changes in physical spaces and fluid flows in a model of GBM after Avastin administration.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review

Simple Summary

An accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Abstract

Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Reproducibility, reliability and variability of FA and MD in the older healthy population: A test-retest multiparametric analysis

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In older healthy subjects, FA and MD show overall good test-retest reliability & reproducibility.

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MD is sistematically more reproducible than FA across the entire brain anatomy.

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FA is more reliable than MD in subcortical white matter regions.

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In high reliability & low reproducibility regions, variability between subjects is high and statistical power is low.

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In low reliability & high reproducibility regions, variability between subjects is low and statistical power is high.

Imaging-guided precision medicine in glioblastoma patients treated with immune checkpoint modulators: research trend and future directions in the field of imaging biomarkers and artificial intelligence

Immunotherapies that employ immune checkpoint modulators (ICMs) have emerged as an effective treatment for a variety of solid cancers, as well as a paradigm shift in the treatment of cancers. Despite this breakthrough, the median survival time of glioblastoma patients has remained at about 2 years. Therefore, the safety and anti-cancer efficacy of combination therapies that include ICMs are being actively investigated. Because of the distinct mechanisms of ICMs, which restore the immune system’s anti-tumor capacity, unconventional immune-related phenomena are increasingly being reported in terms of tumor response and progression, as well as adverse events. Indeed, immunotherapy response assessments for neuro-oncology (iRANO) play a central role in guiding cancer patient management and define a “wait and see strategy” for patients treated with ICMs in monotherapy with progressive disease on MRI. This article deciphers emerging research trends to ameliorate four challenges unaddressed by the iRANO criteria: (1) patient selection, (2) identification of immune-related phenomena other than pseudoprogression (i.e., hyperprogression, the abscopal effect, immune-related adverse events), (3) response assessment in combination therapies including ICM, and (4) alternatives to MRI. To this end, our article provides a structured approach for standardized selection and reporting of imaging modalities to enable the use of precision medicine by deciphering the characteristics of the tumor and its immune environment. Emerging preclinical or clinical innovations are also discussed as future directions such as immune-specific targeting and implementation of artificial intelligence algorithms.

Early assessment of recurrent glioblastoma response to bevacizumab treatment by diffusional kurtosis imaging: a preliminary report

PURPOSE

The purpose of this preliminary study is to apply diffusional kurtosis imaging to assess the early response of recurrent glioblastoma to bevacizumab treatment.

METHODS

This prospective cohort study included 10 patients who had been diagnosed with recurrent glioblastoma and scheduled to receive bevacizumab treatment. Diffusional kurtosis images were obtained from all the patients 0-7 days before (pre-bevacizumab) and 28 days after (post-bevacizumab) initiating bevacizumab treatment. The mean, 10th, and 90th percentile values were derived from the histogram of diffusional kurtosis imaging metrics in enhancing and non-enhancing lesions, selected on post-contrast T1-weighted and fluid-attenuated inversion recovery images. Correlations of imaging measures with progression-free survival and overall survival were evaluated using Spearman's rank correlation coefficient. The significance level was set at P < 0.05.

RESULTS

Higher pre-bevacizumab non-enhancing lesion volume was correlated with poor overall survival (r = -0.65, P = 0.049). Higher post-bevacizumab mean diffusivity and axial diffusivity (D_∥, D_∥10% and D_∥90%) in non-enhancing lesions were correlated with poor progression-free survival (r = -0.73, -0.83, -0.71 and -0.85; P < 0.05). Lower post-bevacizumab axial kurtosis (K_∥10%) in non-enhancing lesions was correlated with poor progression-free survival (r = 0.81, P = 0.008).

CONCLUSIONS

This preliminary study demonstrates that diffusional kurtosis imaging metrics allow the detection of tissue changes 28 days after initiating bevacizumab treatment and that they may provide information about tumor progression.

Quantitative evaluation of diffusion tensor imaging for clinical management of glioma

Diffusion tensor imaging (DTI), assessing physiological motion of water in vivo, provides macroscopic view of microstructures of white matter in the central nervous system, and such imaging technique had been extensively used for the clinical treatment and research of glioma. This review mainly focuses on illuminating the merits of quantitative evaluation of DTI for glioma management. The content of the article includes DTI's application on tissue characterization, white matter tracts mapping, radiotherapy delineation, post-therapy outcome assessment, and multimodal imaging. At last, we elucidate a synoptic presentation of DTI limitation, which is critical for physicians making DTI-based clinical decisions in glioma management.

Survival prediction based on qualitative MRI diffusion signature in patients with recurrent high grade glioma treated with bevacizumab

Background

Bevacizumab was approved by the FDA for the treatment of recurrent or progressive glioblastoma (GBM). Imaging responses are typically assessed by gadolinium-enhanced MRI. We sought to determine the significance of qualitative diffusion signature (manifest as variable degree of dark signal) on ADC maps in recurrent gliomas after treatment with bevacizumab.

Methods

We performed an institutional review board (IRB) approved retrospective study on patients who underwent MRI of the brain after 8 weeks of receiving bevacizumab for recurrent glioma. Patients were divided into three groups based on qualitative diffusion signature: (I) lesion not bright on diffusion weighted imaging (DWI) suggestive of no restricted diffusion (FDR₀); (II) lesion bright on DWI with corresponding homogenous dark signal on apparent diffusion coefficient (ADC) maps suggestive of focal restricted diffusion likely due to bevacizumab induced necrosis (FDR_n); and (III) lesion bright on DWI with corresponding homogenous faint dark signal on ADC maps suggestive of focal restricted diffusion likely due to viable tumor or heterogeneous spectrum of dark and faint dark signals on ADC maps suggestive of focal restricted diffusion likely due to viable tumor surrounding the bevacizumab induced necrosis (FDR_t).

Results

Based on the qualitative signal on diffusion weighted sequences after bevacizumab therapy, total number of patients in group (I) were 14 (36%), in group (II) were 17 (44%); and in group (III) were 8 (20%). The median overall survival (OS) from the time of recurrence in patients belonging to group (II) was 364 days vs. 183 days for those with group (I) vs. 298 days for group (III). On simultaneous comparison of survival differences in all three groups by Kaplan-Meier analysis, group (II) was significant in predicting survival with P values for the log-rank tests <0.033.

Conclusions

In patients with recurrent glioma treated with bevacizumab, the presence of homogenous dark signal (FDR_n) on ADC maps at 8 weeks follow-up MRI correlated with a longer survival. Thus, use of this qualitative diffusion signature in adjunct to contrast enhanced MRI may have the widest potential impact on routine clinical care for patients with recurrent high-grade gliomas. However, prospective studies analysing its predictive value are warranted.

Apparent diffusion coefficient changes predict survival after intra-arterial bevacizumab treatment in recurrent glioblastoma

PURPOSE

Superselective intra-arterial cerebral infusion (SIACI) of bevacizumab (BV) has emerged as a novel therapy in the treatment of recurrent glioblastoma (GB). This study assessed the use of apparent diffusion coefficient (ADC) in predicting length of survival after SIACI BV and overall survival in patients with recurrent GB.

METHODS

Sixty-five patients from a cohort enrolled in a phase I/II trial of SIACI BV for treatment of recurrent GB were retrospectively included in this analysis. MR imaging with a diffusion-weighted (DWI) sequence was performed before and after treatment. ROIs were manually delineated on ADC maps corresponding to the enhancing and non-enhancing portions of the tumor. Cox and logistic regression analyses were performed to determine which ADC values best predicted survival.

RESULTS

The change in minimum ADC in the enhancing portion of the tumor after SIACI BV therapy was associated with an increased risk of death (hazard ratio = 2.0, 95% confidence interval(CI) [1.04-3.79], p = 0.038), adjusting for age, tumor size, BV dose, and prior IV BV treatments. Similarly, the change in ADC after SIACI BV therapy was associated with greater likelihood of surviving less than 1 year after therapy (odds ratio = 7.0, 95% CI [1.08-45.7], p = 0.04). Having previously received IV BV was associated with increased risk of death (OR 18, 95% CI [1.8-180.0], p = 0.014).

CONCLUSION

In patients with recurrent GB treated with SIACI BV, the change in ADC value after treatment is predictive of overall survival.

The Prognosis of Anti-Angiogenesis Treatments Combined with Standard Therapy for Newly Diagnosed Glioblastoma: A Meta-Analysis of Randomized Controlled Trials

BACKGROUND AND PURPOSE

Although bevacizumab (BV) has been approved as second-line therapy for recurrent glioblastoma (GB), the efficacy and safety of BV for patients with newly diagnosed GB remain unclear.

METHODOLOGY/PRINCIPAL FINDINGS

We systematically searched electronic databases (PubMed, EMBASE, OVID, etc.) to identify related studies published from January 1966 and August 2016. Eight randomized controlled trials including a total of 2,185 patients with GB were included. We found that the median progression-free survival (PFS) was higher in the BV group than in the standard therapy (ST) group (pooled hazard ratio, 0.73; 95%CI, 0.62-0.86; P = 0.0001). Compared with ST, BV improved the PFS rate at 6 months (OR 3.33, 95% CI 2.73-4.06, p<0.00001) and 12 months (OR 2.10, 95% CI 1.74-2.54, p<0.00001). There were no significant differences in median overall survival between the BV and ST groups (OR, 1.01; 95%CI, 0.83-1.23; P = 0.95). The BV group had higher survival rates at 6 months (OR, 1.41; 95% CI, 1.09-1.84; P = 0.01) and 12 months (OR, 1.23; 95% CI, 1.02-1.48; P = 0.03), but a low survival rate at the 36-month follow-up (OR, 0.57; 95% CI, 0.32-0.98; P = 0.04). For the incidence of adverse events, three adverse outcomes were found to be significantly different between BV and ST groups, including hypertension (8.37% vs. 1.62%, p<0.000001), proteinuria (7.65% vs. 0%, p<0.001), and fatigue (14.54% vs. 9.01%, p = 0.05).

CONCLUSIONS/SIGNIFICANCE

Our study indicates that combination of BV with ST for newly diagnosed GB did not improve the median overall survival but result in longer median PFS, maintaining the quality of life and functional status. However, the long-term use of BV is associated with a higher incidence of adverse events and mortality.

STUDY REGISTRATION

This research was registered at PROSPERO. (Registration Number: CRD42016038247).

Demonstration of DCE-MRI as an early pharmacodynamic biomarker of response to VEGF Trap in glioblastoma

Glioblastoma (GBM) is an incurable brain tumor characterized by the expression of pro-angiogenic cytokines. A recent phase II clinical trial studied VEGF Trap in adult patients with temozolomide-resistant GBM. We sought to explore changes in [¹⁸F]Fluorodeoxyglucose positron emission tomography (FDG-PET) or magnetic resonance imaging (MRI) in trial participants correlating these changes with disease response. FDG-PET and MRI images obtained before and after the first dose of VEGF Trap were spatially co-registered. Regions of interest on each image slice were combined to produce a volume of interest representative of the entire tumor. Percent and absolute changes in maximum FDG-avidity, mean apparent diffusion coefficient (ADC), K_trans, and Ve were calculated per lesion. Among the 12 participants that underwent dynamic contrast enhanced MRI (DCE-MRI), there were large, statistically significant reductions in K_trans and Ve (median difference = -41.8 %, p < 0.02 and -42.6 %, p < 0.04, respectively). In contrast, there were no significant reductions in ADC or FDG-PET SUVmax values. DCE-MRI is a useful measure of early pharmacodynamic effects of VEGF Trap on tumor vasculature. The absence of significant changes in FDG-PET and DW-MRI suggest that the early pharmacodynamic effects are specific to tumor perfusion and/or permeability and do not directly inhibit metabolism or induce cell death. DCE-MRI in conjunction with standard imaging may be promising for the identification of anti-angiogenic effects in this patient population with this therapeutic target. Further studies are needed to evaluate the relationship between DCE-MRI response and clinical outcome.

Integrative analysis of diffusion-weighted MRI and genomic data to inform treatment of glioblastoma

Gene expression profiling from glioblastoma (GBM) patients enables characterization of cancer into subtypes that can be predictive of response to therapy. An integrative analysis of imaging and gene expression data can potentially be used to obtain novel biomarkers that are closely associated with the genetic subtype and gene signatures and thus provide a noninvasive approach to stratify GBM patients. In this retrospective study, we analyzed the expression of 12,042 genes for 558 patients from The Cancer Genome Atlas (TCGA). Among these patients, 50 patients had magnetic resonance imaging (MRI) studies including diffusion weighted (DW) MRI in The Cancer Imaging Archive (TCIA). We identified the contrast enhancing region of the tumors using the pre- and post-contrast T1-weighted MRI images and computed the apparent diffusion coefficient (ADC) histograms from the DW-MRI images. Using the gene expression data, we classified patients into four molecular subtypes, determined the number and composition of genes modules using the gap statistic, and computed gene signature scores. We used logistic regression to find significant predictors of GBM subtypes. We compared the predictors for different subtypes using Mann-Whitney U tests. We assessed detection power using area under the receiver operating characteristic (ROC) analysis. We computed Spearman correlations to determine the associations between ADC and each of the gene signatures. We performed gene enrichment analysis using Ingenuity Pathway Analysis (IPA). We adjusted all p values using the Benjamini and Hochberg method. The mean ADC was a significant predictor for the neural subtype. Neural tumors had a significantly lower mean ADC compared to non-neural tumors ([Formula: see text]), with mean ADC of [Formula: see text] and [Formula: see text] for neural and non-neural tumors, respectively. Mean ADC showed an area under the ROC of 0.75 for detecting neural tumors. We found eight gene modules in the GBM cohort. The mean ADC was significantly correlated with the gene signature related with dendritic cell maturation ([Formula: see text], [Formula: see text]). Mean ADC could be used as a biomarker of a gene signature associated with dendritic cell maturation and to assist in identifying patients with neural GBMs, known to be resistant to aggressive standard of care.

Imaging of the Posttherapeutic Brain

This review covers important topics relating to the imaging evaluation of glioblastoma multiforme after therapy. An overview of the Macdonald and Response Assessment in Neuro-Oncology criteria as well as important questions and limitations regarding their use are provided. Pseudoprogression and pseudoresponse as well as the use of advanced magnetic resonance imaging techniques such as perfusion, diffusion, and spectroscopy in the evaluation of the posttherapeutic brain are also reviewed.

Evaluation of pre-radiotherapy apparent diffusion coefficient (ADC): patterns of recurrence and survival outcomes analysis in patients treated for glioblastoma multiforme

PURPOSE

To investigate the association of pre-radiotherapy apparent diffusion coefficient (ADC) abnormalities with patterns of recurrence and outcomes in patients with glioblastoma multiforme (GBM).

MATERIALS AND METHODS

Fifty-two patients with recurrent GBM were retrospectively evaluated. Diffusion MRI images were acquired for all patients postoperatively prior to radiotherapy. ADC images were evaluated for geographic regions of diffusion restriction (hypointensity) within the FLAIR volume. If identified, the ADC map and the T1+C MRI at the time of recurrence were registered to the original plan to determine the pattern of recurrence and the coverage of the ADC abnormality by the 60 Gy isodose line (IDL). Progression-free and overall survival was determined for patients with and without an ADC hypointensity.

RESULTS

An ADC hypointensity was identified in 32 (62%) of cases. The recurrence pattern in these cases was central in 27/32 (84%), marginal in 4/32 (13%) and distant in 1/32 (3%). The recurrence overlapped with the ADC hypointensity in 28 (88%) patients. The ADC hypointensity was covered by 95% of the 60 Gy IDL in all cases. Kaplan-Meier analysis revealed inferior progression free survival and overall survival in patients with an ADC hypointensity compared to those without, despite similarities between the groups in terms of age, RT dose, performance status, and extent of resection.

CONCLUSIONS

The presence of an ADC hypointensity on pre-radiotherapy diffusion-weighted imaging is associated with the location of tumor recurrence as demonstrated by frequent overlap in this series, and is associated with a trend toward inferior outcomes. This abnormality may reflect a high risk region of hypercellularity and warrants consideration with respect to radiotherapy planning.

The role of imaging in the management of progressive glioblastoma : a systematic review and evidence-based clinical practice guideline

QUESTION

Which imaging techniques most accurately differentiate true tumor progression from pseudo-progression or treatment related changes in patients with previously diagnosed glioblastoma?

TARGET POPULATION

These recommendations apply to adults with previously diagnosed glioblastoma who are suspected of experiencing progression of the neoplastic process.

RECOMMENDATIONS LEVEL II

Magnetic resonance imaging with and without gadolinium enhancement is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma.

LEVEL II

Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

LEVEL III

The routine use of positron emission tomography to identify progression of glioblastoma is not recommended.

LEVEL III

Single-photon emission computed tomography imaging is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

Emerging biomarkers in glioblastoma

Glioblastoma, the most common primary brain tumor, has few available therapies providing significant improvement in survival. Molecular signatures associated with tumor aggressiveness as well as with disease progression and their relation to differences in signaling pathways implicated in gliomagenesis have recently been described. A number of biomarkers which have potential in diagnosis, prognosis and prediction of response to therapy have been identified and along with imaging modalities could contribute to the clinical management of GBM. Molecular biomarkers including O(6)-methlyguanine-DNA-methyltransferase (MGMT) promoter and deoxyribonucleic acid (DNA) methylation, loss of heterozygosity (LOH) of chromosomes 1p and 19q, loss of heterozygosity 10q, isocitrate dehydrogenase (IDH) mutations, epidermal growth factor receptor (EGFR), epidermal growth factor, latrophilin, and 7 transmembrane domain-containing protein 1 on chromosome 1 (ELTD1), vascular endothelial growth factor (VEGF), tumor suppressor protein p53, phosphatase and tensin homolog (PTEN), p16INK4a gene, cytochrome c oxidase (CcO), phospholipid metabolites, telomerase messenger expression (hTERT messenger ribonucleic acid [mRNA]), microRNAs (miRNAs), cancer stem cell markers and imaging modalities as potential biomarkers are discussed. Inclusion of emerging biomarkers in prospective clinical trials is warranted in an effort for more effective personalized therapy in the future.

Emerging biomarkers in glioblastoma

Glioblastoma, the most common primary brain tumor, has few available therapies providing significant improvement in survival. Molecular signatures associated with tumor aggressiveness as well as with disease progression and their relation to differences in signaling pathways implicated in gliomagenesis have recently been described. A number of biomarkers which have potential in diagnosis, prognosis and prediction of response to therapy have been identified and along with imaging modalities could contribute to the clinical management of GBM. Molecular biomarkers including O(6)-methlyguanine-DNA-methyltransferase (MGMT) promoter and deoxyribonucleic acid (DNA) methylation, loss of heterozygosity (LOH) of chromosomes 1p and 19q, loss of heterozygosity 10q, isocitrate dehydrogenase (IDH) mutations, epidermal growth factor receptor (EGFR), epidermal growth factor, latrophilin, and 7 transmembrane domain-containing protein 1 on chromosome 1 (ELTD1), vascular endothelial growth factor (VEGF), tumor suppressor protein p53, phosphatase and tensin homolog (PTEN), p16INK4a gene, cytochrome c oxidase (CcO), phospholipid metabolites, telomerase messenger expression (hTERT messenger ribonucleic acid [mRNA]), microRNAs (miRNAs), cancer stem cell markers and imaging modalities as potential biomarkers are discussed. Inclusion of emerging biomarkers in prospective clinical trials is warranted in an effort for more effective personalized therapy in the future.

Early post-bevacizumab progression on contrast-enhanced MRI as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 Central Reader Study

BACKGROUND

RTOG 0625/ACRIN 6677 is a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma (GBM). This study investigated whether early posttreatment progression on FLAIR or postcontrast MRI assessed by central reading predicts overall survival (OS).

METHODS

Of 123 enrolled patients, 107 had baseline and at least 1 posttreatment MRI. Two central neuroradiologists serially measured bidimensional (2D) and volumetric (3D) enhancement on postcontrast T1-weighted images and volume of FLAIR hyperintensity. Progression status on all posttreatment MRIs was determined using Macdonald and RANO imaging threshold criteria, with a third neuroradiologist adjudicating discrepancies of both progression occurrence and timing. For each MRI pulse sequence, Kaplan-Meier survival estimates and log-rank test were used to compare OS between cases with or without radiologic progression.

RESULTS

Radiologic progression occurred after 2 chemotherapy cycles (8 weeks) in 9 of 97 (9%), 9 of 73 (12%), and 11 of 98 (11%) 2D-T1, 3D-T1, and FLAIR cases, respectively, and 34 of 80 (43%), 21 of 58 (36%), and 37 of 79 (47%) corresponding cases after 4 cycles (16 weeks). Median OS among patients progressing at 8 or 16 weeks was significantly less than that among nonprogressors, as determined on 2D-T1 (114 vs 278 days and 214 vs 426 days, respectively; P < .0001 for both) and 3D-T1 (117 vs 306 days [P < .0001] and 223 vs 448 days [P = .0003], respectively) but not on FLAIR (201 vs 276 days [P = .38] and 303 vs 321 days [P = .13], respectively).

CONCLUSION

Early progression on 2D-T1 and 3D-T1, but not FLAIR MRI, after 8 and 16 weeks of anti-vascular endothelial growth factor therapy has highly significant prognostic value for OS in recurrent GBM.

Update on bevacizumab and other angiogenesis inhibitors for brain cancer

INTRODUCTION

Primary and metastatic brain tumors remain a major challenge. The most common primary adult malignant brain tumor, glioblastoma (GBM), confers a dismal prognosis as does the development of CNS metastases for most systemic malignancies. Anti-angiogenic therapy has been a major clinical research focus in neuro-oncology over the past 5 years.

AREAS COVERED

Culmination of this work includes US FDA accelerated approval of bevacizumab for recurrent GBM and the completion of two placebo-controlled Phase III studies of bevacizumab for newly diagnosed GBM. A multitude of anti-angiogenics are in evaluation for neuro-oncology patients but none has thus far surpassed the therapeutic benefit of bevacizumab.

EXPERT OPINION

These agents demonstrate adequate safety and the majority of GBM patients derive benefit. Furthermore, their anti-permeability effect can substantially decrease tumor-associated edema leading to stable or improved neurologic function and quality of life. In particular, anti-angiogenics significantly prolong progression-free survival - a noteworthy achievement in the context of infiltrative and destructive brain tumors like GBM; however, in a manner analogous to other cancers, their impact on overall survival for GBM patients is modest at best. Despite substantial clinical research efforts, many fundamental questions regarding anti-angiogenic agents in brain tumor patients remain unanswered.

Posttreatment evaluation of central nervous system gliomas

Although conventional contrast-enhanced MR imaging remains the standard-of-care imaging method in the posttreatment evaluation of gliomas, recent developments in therapeutic options such as chemoradiation and antiangiogenic agents have caused the neuro-oncology community to rethink traditional imaging criteria. This article highlights the latest recommendations. These recommendations should be viewed as works in progress. As more is learned about the pathophysiology of glioma treatment response, quantitative imaging biomarkers will be validated within this context. There will likely be further refinements to glioma response criteria, although the lack of technical standardization in image acquisition, postprocessing, and interpretation also need to be addressed.

Genetics of glioblastoma: a window into its imaging and histopathologic variability

Glioblastoma is a highly malignant brain tumor that relentlessly defies therapy. Efforts over the past decade have begun to tease out the biochemical details that lead to its aggressive behavior and poor prognosis. There is hope that this new understanding will lead to improved treatment strategies for patients with glioblastoma, in the form of targeted, molecularly based therapies that are individualized to specific changes in individual tumors. However, these new therapies have the potential to fundamentally alter the biologic behavior of glioblastoma and, as a result, its imaging appearance. Knowledge about common genetic alterations and the resultant cellular and tissue changes (ie, induced angiogenesis and abnormal cell survival, proliferation, and invasion) in glioblastomas is important as a basis for understanding imaging findings before treatment. It is equally critical that radiologists understand which genetic pathway is targeted by each specific therapeutic agent or class of agents in order to accurately interpret changes in the imaging appearances of treated tumors.