Jennifer Connelly

Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity

To present comprehensive examinations of the assumptions made in functional diffusion map (fDM) analyses and provide a biological basis for fDM classification.

Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma

BACKGROUND The anti-VEGF antibody, bevacizumab, is standard treatment for patients with recurrent glioblastoma. In this setting, traditional anatomic MRI methods such as post-contrast T1-weighted and T2-weighted imaging are proving unreliable for monitoring response. Here we evaluate the prognostic significance of pre- and posttreatment relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast MRI to predict response to bevacizumab. METHODS Thirty-six participants with recurrent high-grade gliomas who underwent rCBV imaging 60 days before and 20-60 days after starting bevacizumab treatment were enrolled. Tumor regions of interest (ROIs) were determined from deltaT1 maps computed from the difference between standardized post and precontrast T1-weighted images. Both pre- and posttreatment rCBV maps were corrected for leakage and standardized (stdRCBV) to a consistent intensity scale. The Kaplan-Meier method was used to determine if either the pre- or post-bevacizumab stdRCBV within the tumor ROI was predictive of overall survival (OS) or progression free survival (PFS). RESULTS The OS was significantly longer if either the pre- (380d vs 175d; P=.0024) or posttreatment stdRCBV (340d vs 186d; P = .0065) was <4400. The posttreatment stdRCBV was also predictive of PFS (167d vs 78d; P = .0006). When the stdRCBV values were both above versus both below threshold, the OS was significantly worse (100.5d vs 395d; P < .0001). With a 32.5% decrease in stdRCBV, the risk of death was reduced by about 68% but increased by 140% with a 29% increase in stdRCBV. CONCLUSIONS Standardized rCBV is predictive of OS and PFS in patients with recurrent high-grade brain tumor treated with bevacizumab.

Volumetric analysis of functional diffusion maps is a predictive imaging biomarker for cytotoxic and anti-angiogenic treatments in malignant gliomas

Anti-angiogenic agents targeting brain tumor neovasculature may increase progression-free survival in patients with recurrent malignant gliomas. However, when these patients do recur it is not always apparent as an increase in enhancing tumor volume on MRI, which has been the standard of practice for following patients with brain tumors. Therefore alternative methods are needed to evaluate patients treated with these novel therapies. Furthermore, a method that can also provide useful information for the evaluation of conventional therapies would provide an important advantage for general applicability. Diffusion-weighted magnetic resonance imaging (DWI) has the potential to serve as a valuable biomarker for these purposes. In the current study, we explore the prognostic ability of functional diffusion maps (fDMs), which examine voxel-wise changes in the apparent diffusion coefficient (ADC) over time, applied to regions of fluid-attenuated inversion recovery (FLAIR) abnormalities in patients with malignant glioma, treated with either anti-angiogenic or cytotoxic therapies. Results indicate that the rate of change in fDMs is an early predictor of tumor progression, time to progression and overall survival for both treatments, suggesting the application of fDMs in FLAIR abnormal regions may be a significant advance in brain tumor biomarker technology.

Photodynamic therapy (PDT) for malignant brain tumors — Where do we stand?

INTRODUCTION What is the current status of photodynamic therapy (PDT) with regard to treating malignant brain tumors? Despite several decades of effort, PDT has yet to achieve standard of care. PURPOSE The questions we wish to answer are: where are we clinically with PDT, why is it not standard of care, and what is being done in clinical trials to get us there. METHOD Rather than a meta-analysis or comprehensive review, our review focuses on who the major research groups are, what their approaches to the problem are, and how their results compare to standard of care. Secondary questions include what the effective depth of light penetration is, and how deep can we expect to kill tumor cells. CURRENT RESULTS A measurable degree of necrosis is seen to a depth of about 5mm. Cavitary PDT with hematoporphyrin derivative (HpD) results are encouraging, but need an adequate Phase III trial. Talaporfin with cavitary light application appears promising, although only a small case series has been reported. Foscan for fluorescence guided resection (FGR) plus intraoperative cavitary PDT results were improved over controls, but are poor compared to other groups. 5-Aminolevulinic acid-FGR plus postop cavitary HpD PDT show improvement over controls, but the comparison to standard of care is still poor. CONCLUSION Continued research in PDT will determine whether the advances shown will mitigate morbidity and mortality, but certainly the potential for this modality to revolutionize the treatment of brain tumors remains. The various uses for PDT in clinical practice should be pursued.

Spatially quantifying microscopic tumor invasion and proliferation using a voxel-wise solution to a glioma growth model and serial diffusion MRI

The purpose of this study was to develop a voxel‐wise analytical solution to a glioma growth model using serial diffusion MRI. These cell invasion, motility, and proliferation level estimates (CIMPLE maps) provide quantitative estimates of microscopic tumor growth dynamics. After an analytical solution was found, noise simulations were performed to predict the effects that perturbations in apparent diffusion coefficient values and the time between apparent diffusion coefficient map acquisitions would have on the accuracy of CIMPLE maps. CIMPLE maps were then created for 53 patients with gliomas with WHO grades of II–IV. MR spectroscopy estimates of the choline‐to‐N‐acetylaspartate ratio were compared to cell proliferation estimates in CIMPLE maps using Pearsons correlation analysis. Median differences in cell proliferation and diffusion rates between WHO grades were compared. A strong correlation (R2 = 0.9714) and good spatial correspondence were observed between MR spectroscopy measurements of the choline‐to‐N‐acetylaspartate ratio and CIMPLE map cell proliferation rate estimates. Estimates of cell proliferation and diffusion rates appear to be significantly different between low‐ (WHO II) and high‐grade (WHO III–IV) gliomas. Cell diffusion rate (motility) estimates are highly dependent on the time interval between apparent diffusion coefficient map acquisitions, whereas cell proliferation rate estimates are additionally influenced by the level of noise present in apparent diffusion coefficient maps. Magn Reson Med, 2010.

Vascular change measured with independent component analysis of dynamic susceptibility contrast MRI predicts bevacizumab response in high-grade glioma

BACKGROUND Standard pre- and postcontrast (T1 + C) anatomical MR imaging is proving to be insufficient for accurately monitoring bevacizumab treatment response in recurrent glioblastoma (GBM). We present a novel imaging biomarker that detects abnormal tumor vasculature exhibiting both arterial and venous perfusion characteristics. We hypothesized that a decrease in the extent of this abnormal vasculature after bevacizumab treatment would predict treatment efficacy and overall survival. METHODS Dynamic susceptibility contrast perfusion MRI was gathered in 43 patients with high-grade glioma. Independent component analysis separated vasculature into arterial and venous components. Voxels with perfusion characteristics of both arteries and veins (ie, arterio-venous overlap [AVOL]) were measured in patients with de novo untreated GBM and patients with recurrent high-grade glioma before and after bevacizumab treatment. Treated patients were separated on the basis of an increase or decrease in AVOL volume (+/-ΔAVOL), and overall survival following bevacizumab onset was then compared between +/-ΔAVOL groups. RESULTS AVOL in untreated GBM was significantly higher than in normal vasculature (P < .001). Kaplan-Meier survival curves revealed a greater median survival (348 days) in patients with GBM with a negative ΔAVOL after bevacizumab treatment than in patients with a positive change (197 days; hazard ratio, 2.51; P < .05). Analysis of patients with combined grade III and IV glioma showed similar results, with median survivals of 399 days and 153 days, respectively (hazard ratio, 2.71; P < .01). Changes in T1+C volume and ΔrCBV after treatment were not significantly different across +/-ΔAVOL groups, and ΔAVOL was not significantly correlated with ΔT1+C or ΔrCBV. CONCLUSIONS The independent component analysis dynamic susceptibility contrast-derived biomarker AVOL adds additional information for determining bevacizumab treatment efficacy.

Precise ex vivo histological validation of heightened cellularity and diffusion-restricted necrosis in regions of dark apparent diffusion coefficient in 7 cases of high-grade glioma

BACKGROUND Recent conflicting reports have found both brain tumor hypercellularity and necrosis in regions of restricted diffusion on MRI-derived apparent diffusion coefficient (ADC) images. This study precisely compares ADC and cell density voxel by voxel using postmortem human whole brain samples. METHODS Patients with meningioma were evaluated to determine a normative ADC distribution within benign fluid attenuated inversion recovery (FLAIR) T2/hyperintensity surrounding tumor. This distribution was used to calculate a minimum ADC threshold to define regions of ADC-FLAIR mismatch (AFMM), where restricted diffusion presented in conjunction with T2/FLAIR hyperintensity. Contrast-enhancing voxels were excluded from this analysis. AFMM maps were generated using imaging acquired prior to death in 7 patients with high-grade glioma who eventually donated their brains upon death. Histological samples were taken from numerous regions of abnormal FLAIR and AFMM. Each sample was computationally processed to determine cell density. Custom software was then used to downsample coregistered microscopic histology to the more coarse MRI resolution. A voxel-by-voxel evaluation comparing ADC and cellularity was then performed. RESULTS An ADC threshold of 0.929 × 10(-3) mm(2)/s was calculated from meningioma-induced edema and was used to define AFMM. Regions of AFMM showed significantly greater cell density in 6 of 7 high-grade glioma cases compared with regions of hyperintense FLAIR alone (P < .0001). Two patients had small regions of diffusion-restricted necrosis that had significantly lower ADC than nearby hypercellularity. CONCLUSIONS Regions of AFMM contain hypercellularity except for regions with extremely restricted diffusion, where necrosis is present.

Progressing Bevacizumab-Induced Diffusion Restriction Is Associated with Coagulative Necrosis Surrounded by Viable Tumor and Decreased Overall Survival in Patients with Recurrent Glioblastoma

The authors explored regions of diffusion restriction following bevacizumab therapy in patients with glioblastoma by 1) analyzing tissue samples from patients at postmortem to pathologically confirm tumor cellularity or coagulative necrosis and 2) assessing the patient populationto determine the effect that these lesions have on overall survival. The postmortem examinations were performed on 6 patients with recurrent glioblastoma on bevacizumab withprogressively growing regions of diffusion restriction. ADC values were extracted from regions of both hypercellular tumor and necrosis. They conclude that progressive diffusion-restricted lesions were pathologically confirmed to be coagulative necrosis surrounded by viable tumor and associated with decreased overall survival. BACKGROUND AND PURPOSE: Patients with recurrent glioblastoma often exhibit regions of diffusion restriction following the initiation of bevacizumab therapy. Studies suggest that these regions represent either diffusion-restricted necrosis or hypercellular tumor. This study explored postmortem brain specimens and a population analysis of overall survival to determine the identity and implications of such lesions. MATERIALS AND METHODS: Postmortem examinations were performed on 6 patients with recurrent glioblastoma on bevacizumab with progressively growing regions of diffusion restriction. ADC values were extracted from regions of both hypercellular tumor and necrosis. A receiver operating characteristic analysis was performed to define optimal ADC thresholds for differentiating tissue types. A retrospective population study was also performed comparing the overall survival of 64 patients with recurrent glioblastoma treated with bevacizumab. Patients were separated into 3 groups: no diffusion restriction, diffusion restriction that appeared and progressed within 5 months of bevacizumab initiation, and delayed or stable diffusion restriction. An additional analysis was performed assessing tumor O6-methylguanine-DNA-methyltransferase methylation. RESULTS: The optimal ADC threshold for differentiation of hypercellularity and necrosis was 0.736 × 10−3mm2/s. Progressively expanding diffusion restriction was pathologically confirmed to be coagulative necrosis surrounded by viable tumor. Progressive lesions were associated with the worst overall survival, while stable lesions showed the greatest overall survival (P < .05). Of the 40% of patients with O6-methylguanine-DNA-methyltransferase methylated tumors, none developed diffusion-restricted lesions. CONCLUSIONS: Progressive diffusion-restricted lesions were pathologically confirmed to be coagulative necrosis surrounded by viable tumor and associated with decreased overall survival. Stable lesions were, however, associated with increased overall survival. All lesions were associated with O6-methylguanine-DNA-methyltransferase unmethylated tumors.

Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics

Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNNα was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.

Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy

Magnetic resonance imaging (MRI) is used to diagnose and monitor brain tumors. Extracting additional information from medical imaging and relating it to a clinical variable of interest is broadly defined as radiomics. Here, multiparametric MRI radiomic profiles (RPs) of de novo glioblastoma (GBM) brain tumors is related with patient prognosis. Clinical imaging from 81 patients with GBM before surgery was analyzed. Four MRI contrasts were aligned, masked by margins defined by gadolinium contrast enhancement and T2/fluid attenuated inversion recovery hyperintensity, and contoured based on image intensity. These segmentations were combined for visualization and quantification by assigning a 4-digit numerical code to each voxel to indicate the segmented RP. Each RP volume was then compared with overall survival. A combined classifier was then generated on the basis of significant RPs and optimized volume thresholds. Five RPs were predictive of overall survival before therapy. Combining the RP classifiers into a single prognostic score predicted patient survival better than each alone (P < .005). Voxels coded with 1 RP associated with poor prognosis were pathologically confirmed to contain hypercellular tumor. This study applies radiomic profiling to de novo patients with GBM to determine imaging signatures associated with poor prognosis at tumor diagnosis. This tool may be useful for planning surgical resection or radiation treatment margins.