Peritumoral apparent diffusion coefficient as a metric of response in patients with recurrent glioblastoma multiforme treated with bevacizumab and irinotecan

Treatment Response and Prognosis Evaluation in High-Grade Glioma: An Imaging Review Based on MRI

In recent years, the development of advanced magnetic resonance imaging (MRI) technology and machine learning (ML) have created new tools for evaluating treatment response and prognosis of patients with high-grade gliomas (HGG); however, patient prognosis has not improved significantly. This is mainly due to the heterogeneity between and within HGG tumors, resulting in standard treatment methods not benefitting all patients. Moreover, the survival of patients with HGG is not only related to tumor cells, but also to noncancer cells in the tumor microenvironment (TME). Therefore, during preoperative diagnosis and follow-up treatment of patients with HGG, noninvasive imaging markers are needed to characterize intratumoral heterogeneity, and then to evaluate treatment response and predict prognosis, timeously adjust treatment strategies, and achieve individualized diagnosis and treatment. In this review, we summarize the research progress of conventional MRI, advanced MRI technology, and ML in evaluation of treatment response and prognosis of patients with HGG. We further discuss the significance of the TME in the prognosis of HGG patients, associate imaging features with the TME, indirectly reflecting the heterogeneity within the tumor, and shifting treatment strategies from tumor cells alone to systemic therapy of the TME, which may be a major development direction in the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 4.

Apparent diffusion coefficient and tumor volume measurements help stratify progression-free survival of bevacizumab-treated patients with recurrent glioblastoma multiforme

BACKGROUND

The aim of this study was to determine whether apparent diffusion coefficient (ADC) bi-component curve-fitting histogram analysis and volume percentage change (VPC) prior to bevacizumab treatment can stratify progression-free survival (PFS) and overall survival (OS) in patients with glioblastoma multiforme (GBM) on first recurrence.

METHODS

We retrospectively evaluated 17 patients with recurrent GBM who received bevacizumab and fotemustine (n = 13) or only bevacizumab (n = 4) on first recurrence at our institution between December 2009 and July 2015. Both T2/FLAIR abnormalities and enhancing tumor on T1 images were mapped to the ADC images. ADC-L and ADC-M values were obtained trough bi-Gaussian curve fitting histogram analysis. Furthermore, the study population was dichotomized into two subgroups: patients displaying a reduction in enhancing tumor volume of either >55% or <55% between the mean value calculated at baseline and first follow-up. Subsequently, a second dichotomization was performed according to a reduction in the T2 / FLAIR volume >41% or <41% at first check after treatment. OS and PFS were assessed using volume parameters in a Cox regression model adjusted for significant clinical parameters.

RESULTS

In univariate analysis, contrast-enhanced (CE)-ADC-L was significantly predictive of PFS (p = 0.01) and OS (p = 0.03). When we dichotomized our sample using the 55% cut-off for enhancing tumor volume, CE-VPC was able to predict PFS (p = 0.01) but not OS (p = 0.08). In multivariate analysis, only the CE-ADC-L was predictive of PFS (p = 0.01), albeit not predictive of OS (p = 0.14). CE-ADC-M, T2/FLAIR-ADC-L, T2/FLAIR-ADC, and T2/FLAIR VPC were not significantly predictive of PFS and OS (p > 0.05) in both univariate and multivariate analysis.

CONCLUSIONS

CE-ADC and CE-VPC can stratify PFS for patients with recurrent glioblastoma prior to bevacizumab treatment.

Posttreatment Evaluation of Brain Gliomas

The imaging of treated gliomas is complicated by a variety of treatment related effects, which can falsely simulate disease improvement or progression. Distinguishing between disease progression and treatment effects is difficult with standard MR imaging pulse sequences and added specificity can be gained by the addition of advanced imaging techniques.

Cerebral Blood Flow Changes in Glioblastoma Patients Undergoing Bevacizumab Treatment Are Seen in Both Tumor and Normal Brain

Bevacizumab (BEV) is increasingly used to treat recurrent glioblastoma (GBM) with some reported improvement in neurocognitive function despite potential neurotoxicities. We examined the effects of BEV on cerebral blood flow (CBF) within recurrent GBM tumor and in the contralateral middle cerebral artery (MCA) territory.Post-chemoradiation patients with histologically confirmed GBM were treated with BEV and underwent routine, serial tumor imaging with additional pseudocontinuous arterial spin labeling (pcASL) following informed consent. Circular regions-of-interest were placed on pcASL images directly over the recurrent tumor and in the contralateral MCA territory. CBF changes before and during BEV treatment were evaluated in tumor and normal tissue. Linear mixed models were used to assess statistical significance.Fifty-three pcASL studies in 18 patients were acquired. Evaluation yielded lower mean tumoral CBF during BEV treatment compared with pre-treatment (45 ± 27 vs. 65 ± 27 ml/100 g/min, p = 0.002), and in the contralateral MCA territory during, compared with pre-BEV treatment (35 ± 8.4 vs. 41 ± 8.4 ml/100 g/min, p = 0.03). The decrease in mean CBF tended to be greater in the tumoral region than in the contralateral MCA, though the difference did not reach statistical significance (31% vs. 13%; p = 0.082).

CONCLUSIONS

BEV administration results in statistically significant global CBF decrease with a potentially preferential decrease in tumor perfusion compared with normal brain tissue.

Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma

BACKGROUND AND PURPOSE

Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme.

MATERIALS AND METHODS

Eighty-nine bevacizumab-treated and 43 chemotherapy-treated recurrent glioblastoma multiformes never exposed to bevacizumab were included in this study. In all patients, ADC values in contrast-enhancing ROIs from MR imaging examinations performed at the time of recurrence, immediately before commencement of treatment for recurrence, were extracted and the resulting histogram was fitted to a mixed model with a double Gaussian distribution. Mean ADC in the lower Gaussian curve was used as the primary biomarker of interest. The Cox proportional hazards model and log-rank tests were used for survival analysis.

RESULTS

Cox multivariate regression analysis accounting for the interaction between bevacizumab- and non-bevacizumab-treated patients suggested that the ability of the lower Gaussian curve to predict survival is dependent on treatment (progression-free survival, P = .045; overall survival, P = .003). Patients with bevacizumab-treated recurrent glioblastoma multiforme with a pretreatment lower Gaussian curve > 1.2 μm(2)/ms had a significantly longer progression-free survival and overall survival compared with bevacizumab-treated patients with a lower Gaussian curve < 1.2 μm(2)/ms. No differences in progression-free survival or overall survival were observed in the chemotherapy-treated cohort. Bevacizumab-treated patients with a mean lower Gaussian curve > 1.2 μm(2)/ms had a significantly longer progression-free survival and overall survival compared with chemotherapy-treated patients.

CONCLUSIONS

The mean lower Gaussian curve from ADC histogram analysis is a predictive imaging biomarker for bevacizumab-treated, not chemotherapy-treated, recurrent glioblastoma multiforme. Patients with recurrent glioblastoma multiforme with a mean lower Gaussian curve > 1.2 μm(2)/ms have a survival advantage when treated with bevacizumab.