Predictive significance of mean apparent diffusion coefficient value for responsiveness of temozolomide-refractory malignant glioma to bevacizumab: preliminary report

Analyzing the role of reoperation in recurrent glioblastoma: a 15-year retrospective study in a single institution

BACKGROUND

Multiple treatment options at glioblastoma progression exist, including reintervention, reirradiation, additional systemic therapy, and novel strategies. No alternative has been proven to be superior in terms of postprogression survival (PPS). A second surgery has shown conflicting evidence in the literature regarding its prognostic impact, possibly affected by selection bias, and might benefit a sparse subset of patients with recurrent glioblastoma. The present study aims to determine the prognostic influence of salvage procedures in a cohort of patients treated in the same institution over 15 years.

METHODS

Three hundred and fifty patients with confirmed primary glioblastoma diagnosed and treated between 2005 and 2019 were selected. To examine the role of reoperation, we intended to create comparable groups, previously excluding all diagnostic biopsies and patients who were not actively treated after the first surgery or at disease progression. Uni- and multivariate Cox proportional hazards regression models were employed, considering reintervention as a time-fixed or time-dependent covariate. The endpoints of the study were overall survival (OS) and PPS.

RESULTS

At progression, 33 patients received a second surgery and 84 were treated with chemotherapy only. Clinical variables were similar among groups. OS, but not PPS, was superior in the reintervention group. Treatment modality had no impact in our multivariate Cox regression models considering OS or PPS as the endpoint.

CONCLUSIONS

The association of reoperation with improved prognosis in recurrent glioblastoma is unclear and may be influenced by selection bias. Regardless of our selective indications and high gross total resection rates in second procedures, we could not observe a survival advantage.

Diagnostic accuracy of diffusion-weighted imaging in differentiating glioma recurrence from posttreatment-related changes: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is the most commonly used imaging method to evaluate glioma recurrence. However, conventional MRI has difficulty distinguishing glioma accurately. This study aimed to explore the value of diffusion weighted imaging (DWI) in evaluating glioma recurrence and post-treatment-related changes.

RESEARCH DESIGN AND METHODS

PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science and Technology Journal Database were extensively searched in accordance with inclusion criteria and exclusion criteria to obtain appropriate included studies. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Combined sensitivity and specificity and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated.

RESULTS

Seventeen high-quality studies were included. The combined sensitivity was 0.82 (95% CI: 0.76-0.87), the specificity was 0.83 (95% CI: 0.76-0.89), the positive likelihood ratio was 4.9 (95% CI: 3.2-7.5), the negative likelihood ratio was 0.21 (95% CI: 0.15-0.30), the diagnostic odds ratio was 23 (95%: CI 11-48), and the area under the SROC was 0.90 (95% CI: 0.87-0.92).

CONCLUSIONS

This meta-analysis suggests that DWI has high sensitivity, specificity and accuracy in differentiating glioma recurrence.

Predictive effect of DCE-MRI and DWI in brain metastases from NSCLC

Non-small cell lung cancer (NSCLC), a commonly diagnosed lung cancer, is characterized by a high incidence of metastatic spread to the brain, which adversely impacts prognosis. The present study aimed to assess the value of combined dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in predicting the treatment outcomes of whole-brain radiotherapy (WBRT) and gefitinib in brain metastases from non-small cell lung cancer (NSCLC) from the perspectives of response rate and short- and long-term efficacy. These results suggested that the indicators measured by DCE-MRI combined with DWI can be used as key imaging-derived markers that predicted the efficacy of WBRT combined with gefitinib in NSCLC patients with brain metastases. Specifically, patients with higher ΔADC_mid and ΔADC_post values showed better treatment outcomes. ROC curve analysis indicated ADC_post, ΔADC_post, ΔADC_post (%), and tumor regression rate as the best predictors of efficacy of WBRT combined with gefitinib in these patients. The short-term and long-term effects noted were also significant. Taken together, the findings of this study reveal that tumor regression rate, ADC_post, ΔADC_post, and ΔADC_post (%) can be used as important imaging indicators that predict the therapeutic effect of WBRT combined with gefitinib in NSCLC patients with brain metastases.

Long-term apparent diffusion coefficient value changes in patients undergoing radiosurgical treatment of meningiomas

PURPOSE

A noninvasive method to predict the progress or treatment response of meningiomas is desirable to improve the tumor management. Studies showed that apparent diffusion coefficient (ADC) pretreatment values can predict treatment response in brain tumors. The aim of this study was to analyze changes of intratumoral ADC values in patients with meningiomas undergoing conservative or radiosurgery.

METHOD

MR images of 51 patients with diagnose of meningiomas were retrospectively reviewed. Twenty-five patients undergoing conservative or radiosurgery treatment, respectively, were included in the study. The follow-up data ranged between 1 and 10 years. Based on ROI analysis, the mean ADC values, ADC_10%min, and ADC_90%max were evaluated at different time points during follow-up.

RESULTS

Baseline ADC values in between both groups were similar. The ADC_mean values, ADC_10%min, and ADC_90%max within the different groups did not show any significant changes during the follow-up times in the untreated (ADC_mean over 10 years period: 0.87 ± 0.05 × 10^-3 mm²/s) and radiosurgically treated (ADC_mean over 4 years period: 1.02 ± 0.12 × 10^-3 mm²/s) group. However, statistically significant difference was observed when comparing the ADC_mean and ADC_90%max values of untreated with radiosurgically treated (p < 0.0001) meningiomas. Also, ADC_10%min revealed statistically significant difference between the untreated and the radiosurgery group (p < 0.05).

CONCLUSIONS

ADC values in conservatively managed meningiomas remain stable during the follow-up. However, meningiomas undergoing radiosurgery reveal significant change of the mean ADC values over time, suggesting that ADC may reflect a change in the biological behavior of the tumor. These observations might suggest the value of ADC changes as an indicator of treatment response.

Comparison of Voxel-Wise and Histogram Analyses of Glioma ADC Maps for Prediction of Early Therapeutic Change

Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent diffusion coefficient (ADC), have previously shown promise when used in combination with voxel-based analysis reflecting regional changes. The functional diffusion mapping (fDM) metric is hypothesized to be associated with volume of tumor exhibiting an increasing ADC owing to effective therapeutic action. In this work, the reference fDM-predicted survival (from previous study) for 3 weeks from treatment initiation (midtreatment) is compared to multiple histogram-based metrics using Kaplan–Meier estimator for 80 glioma patients stratified to responders and nonresponders based on the population median value for the given metric. The ADC histogram metric reflecting reduction in midtreatment volume of solid tumor (ADC < 1.25 × 10⁻³ mm²/s) by >8% population-median with respect to pretreatment is found to have the same predictive power as the reference fDM of increasing midtreatment ADC volume above 4%. This study establishes the level of correlation between fDM increase and low-ADC tumor volume shrinkage for prediction of early response to radiation therapy in patients with glioma malignancies.

Utility of intravoxel incoherent motion magnetic resonance imaging and arterial spin labeling for recurrent glioma after bevacizumab treatment

Background Detecting recurrence of glioma on magnetic resonance imaging (MRI) is getting more and more important, especially after administration of new anti-tumor agent. However, it is still hard to identify. Purpose To examine the utility of intravoxel incoherent motion (IVIM) MRI and arterial spin labeling-cerebral blood flow (ASL-CBF) for recurrent glioma after initiation of bevacizumab (BEV) treatment. Material and Methods Thirteen patients (7 men, 6 women; age range = 41-82 years) with glioma (high grade, n = 11; low grade, n = 2) were enrolled in the study. IVIM parameters including apparent diffusion coefficient (ADC), true diffusion coefficient (D), and perfusion fraction (f) were obtained with 14 different b-values. We identified tumor progression during BEV therapy by MRI monitoring consisting of diffusion-weighted imaging (DWI), fluid-attenuated inversion recovery (FLAIR) imaging, and contrast-enhanced T1-weighted (CE-T1W) imaging by measuring tumor area. We also measured each parameter of IVIM and ASL-CBF, and calculated relative ADC (rADC), relative D (rD), relative f (rf), and relative CBF (rCBF) by obtaining the ratio between each area and the contralateral cerebral white matter. We calculated the rate of change (Δ) by subtracting values from those from the preceding MRI study, and obtained Spearman's rank correlation coefficient (rs). Results Tumor progression was identified in nine patients (high grade, n = 7; low grade, n = 2). Negative correlations were identified between ΔrD and ΔDWI area (rs = -0.583), and between ΔrD and ΔCE-T1W imaging area (rs = -0.605). Conclusion Tumor progression after BEV treatment can be identified by decreasing rD.

Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma

INTRODUCTION

We describe the imaging findings encountered in GBM patients receiving immune checkpoint blockade and assess the potential of quantitative MRI biomarkers to differentiate patients who derive therapeutic benefit from those who do not.

METHODS

A retrospective analysis was performed on longitudinal MRIs obtained on recurrent GBM patients enrolled on clinical trials. Among 10 patients with analyzable data, bidirectional diameters were measured on contrast enhanced T1 (pGd-T1WI) and volumes of interest (VOI) representing measurable abnormality suggestive of tumor were selected on pGdT1WI (pGdT1 VOI), FLAIR-T2WI (FLAIR VOI), and ADC maps. Intermediate ADC (IADC) VOI represented voxels within the FLAIR VOI having ADC in the range of highly cellular tumor (0.7-1.1 × 10^-3 mm²/s) (IADC VOI). Therapeutic benefit was determined by tissue pathology and survival on trial. IADC VOI, pGdT1 VOI, FLAIR VOI, and RANO assessment results were correlated with patient benefit.

RESULTS

Five patients were deemed to have received therapeutic benefit and the other five patients did not. The average time on trial for the benefit group was 194 days, as compared to 81 days for the no benefit group. IADC VOI correlated well with the presence or absence of clinical benefit in 10 patients. Furthermore, pGd VOI, FLAIR VOI, and RANO assessment correlated less well with response.

CONCLUSION

MRI reveals an initial increase in volumes of abnormal tissue with contrast enhancement, edema, and intermediate ADC suggesting hypercellularity within the first 0-6 months of immunotherapy. Subsequent stabilization and improvement in IADC VOI appear to better predict ultimate therapeutic benefit from these agents than conventional imaging.

The predictive capacity of apparent diffusion coefficient (ADC) in response assessment of brain metastases following radiation

To investigate the predictive capacity of the apparent diffusion coefficient (ADC) as a biomarker of radiation response in brain metastases. Seventy brain metastases from 42 patients treated with either stereotactic radiosurgery or whole brain radiotherapy were imaged at baseline, 1 week, and 1 month post-treatment using diffusion-weighted MRI. Mean and median relative ADC for metastases was calculated by normalizing ADC measurements to baseline ADC. At 1 year post-treatment, or last available follow-up MRI, volume criteria determined final tumour response status. Uni- and multivariate analysis was used to account for factors associated with tumour response at 1 week and 1 month. A generalized estimating equations model took into consideration multiple tumours per subject. Optimal thresholds that distinguished responders from non-responders, as well as sensitivity and specificity were determined by receiver operator characteristic analysis and Youden's index. Lower relative ADC values distinguished responders from non-responders at 1 week and 1 month (P < 0.05). Optimal cut-off values for response were 1.060 at 1 week with a sensitivity and specificity of 75.0 and 56.3 %, respectively. At 1 month, the cut-off was 0.971 with a sensitivity and specificity of 70.0 and 68.8 %, respectively. A multivariate general estimating equations analysis identified no prior radiation [odds ratio (OR) 0.211 and 0.137, P = 0.033 and 0.0177], and a lower median relative ADC at 1 week and 1 month (OR 0.619 and 0.694, P = 0.0036 and 0.005), as predictors of tumour response. Lower relative ADC values at 1 week and 1 month following radiation distinguished responders from non-responders and may be a promising biomarker of early radiation response.

Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.

Chronic arterial hypertension impedes glioma growth: a multiparametric MRI study in the rat

Glioblastoma is the most aggressive brain tumor and is almost always fatal. These tumors are highly vascularized and angiogenesis is one of the pre-eminent mechanisms underlying their growth. Chronic arterial hypertension (CAH) is a common and worldwide pathology that markedlly alters the structure and function of the vasculature. Yet, essential hypertension is associated in the brain with potential locally impaired vasoreactivity, disturbed perfusion supply and hypoxia phenomena. Even though CAH is a global burden and has an important impact on brain function, nothing is known about the way this frequent pathology would interact with the evolution of glioma. We sought to determine if arterial hypertension influences gliobastoma growth. In the present study, rat glioma C6 tumor cells were implanted in the caudate-putamen of spontaneously hypertensive rats (SHR) or their normotensive controls, the Wistar-Kyoto (WKY) rats. The evolution of the tumor was sequentially analyzed by multiparametric magnetic resonance imaging and the inflammatory response was examined by histochemistry. We found that CAH significantly attenuates the growth of the tumor as, at 21 days, the volume of the tumor was 85.4±34.7 and 126.1±28.8 mm(3), respectively, in hypertensive and normotensive rats (P<0.02). Moreover, cerebral blood volume and cerebral blood flow were greater in the tumors of hypertensive rats (P<0.05). The lesser growth of the tumor observed in normotensive animals was not due to an enhanced rejection of the tumor cells in WKY rats, the inflammatory response being similar in both groups. For the first time, these results show that CAH impedes the growth of glioblastoma and illustrate the need to further study the impact of hypertension on the evolution of brain tumors.