The extent and severity of vascular leakage as evidence of tumor aggressiveness in high-grade gliomas

Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients

Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the non-enhancing T2 hyperintensity areas using conventional MRI alone. Quantitative DCE MRI parameters such as Ktrans and Ve convey permeability information of glioblastomas that cannot be provided by conventional MRI. We used the publicly available nnU-Net to train a deep learning model that incorporated both conventional and DCE MRI to detect the subtle difference in vessel leakiness due to neoangiogenesis between the non-recurrence area and the local recurrence area, which contains a higher proportion of high-grade glioma cells. We found that the addition of Ve doubled the sensitivity while nonsignificantly decreasing the specificity for prediction of local recurrence in glioblastomas, which implies that the combined model may result in fewer missed cases of local recurrence. The deep learning model predictive of local recurrence may enable risk-adapted radiotherapy planning in patients with grade 4 adult-type diffuse gliomas.

Immune cell identity behind the Ktrans mapping of mouse glioblastoma

Dynamic contrast-enhanced MR imaging (DCE-MRI) can assess the integrity of the blood brain barrier (BBB) and has been used in GBM patients to determine glioma grade, predict prognosis, evaluate treatment response, and differentiate treatment-induced effect from recurrence. The volume transfer constant Ktrans is the most frequently used metric in tumor assessment. Based on previous studies that a higher WHO grade of brain tumor was associated with greater impairments of immunity and that Ktrans value was associated with the pathological grading, the relationship between differential composition of immune cells in GBM tissue and dynamic changes in Ktrans mapping was anticipated in this study. The present study utilized an orthotopic allograft model of GBM in which mouse GL26 cells are implanted into Ccr2RFP/wtCx3cr1GFP/wt mice on a C57 background. The brain tumors exhibited heterogenous Ktrans values with the coefficients of variation (CV) above 75%, or relatively homogeneous Ktrans maps with CV values below 50%. The Ktrans values of homogeneous tumors ranged between 0.02/min-0.32/min with a median value of 0.10/min. The immune cell composition defined by quantitative immunohistochemistry and cell sorting was compared between the tumors with Ktrans values above 0.10/min (higher Ktrans) or below 0.10/min (lower Ktrans). Histological analysis showed that tumors with higher Ktrans values exhibited greater numbers of CCR2pos cells (257.60 ± 16.42/mm2 vs 203.23 ± 12.20/mm2, p = 0.04) and an increased ratio of CCR2pos cells to CX3CR1pos cells (1.20 ± 0.02 vs 0.38 ± 0.04, p = 0.001), the numbers of CX3CR1pos cells did not differ significantly based on Ktrans values (219.70 ± 16.20/mm2 vs 250.38 ± 21.20/mm2, p = 0.19). Flowcytometry analysis showed that tumors with higher Ktrans values (above 0.1/min) were associated with greater numbers of both overall monocytes (54.93 ± 6.81% vs 29.75 ± 3.54%, p = 0.01) and inflammatory monocytes (72.38 ± 1.49% vs 59.52 ± 2.44%, p = 0.001). In contrast, tumors with lower Ktrans values (below 0.1/min) exhibited greater numbers of patrolling monocytes (75.65 ± 4.14% vs 63 ± 6.94%, p = 0.05). In the tumors with lower Ktrans values, all three types of tumor associated cells, including patrolling monocytes, inflammatory monocytes, and microglia cells possessed a higher proportion of cells at pro-inflammatory status (41.77 ± 6.13% vs 25.06 ± 6.72%, p = 0.05; 27.50 ± 2.11% vs 20.62 ± 1.87%, p = 0.03; and 55.80 ± 9.88% vs 31.12 ± 7.31%, p = 0.05), inflammatory monocytes showed fewer anti-inflammatory cells (1.25 ± 0.62% vs 3.16 ± 3.56%, p = 0.04). Taken together, differences in Ktrans values were associated with differential immune cell phenotypes and polarizations. Ktrans mapping may therefore represent a novel approach for defining the immune status of GBM.

Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

A Phase 2 Study of Dose-intensified Chemoradiation Using Biologically Based Target Volume Definition in Patients With Newly Diagnosed Glioblastoma

PURPOSE

We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TVHCV) and hyperperfused (TVCBV) tumor volumes would improve outcomes in patients with glioblastoma.

METHODS AND MATERIALS

This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TVHCV/TVCBV >1 cm3, identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TVHCV/TVCBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TVHCV/TVCBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised.

RESULTS

Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TVHCV alone, and 13 patients were boosted to both TVHCV/TVCBV. Gross or subtotal resection was performed in 87% of patients; 22% were O6-methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TVHCV/TVCBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TVHCV/TVCBV decreased to less than the median volume (3 cm3) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy.

CONCLUSIONS

Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy.

Novel Radiation Approaches

The standard of care treatment for glioblastoma is surgical resection followed by radiotherapy to 60 Gy with concurrent and adjuvant temozolomide with or without tumor-treating fields. Advanced imaging techniques are under evaluation to better guide radiotherapy target volume delineation and allow for dose escalation. Particle therapy, in the form of protons, carbon ions, and boron neutron capture therapy, are being assessed as strategies to improve the radiotherapeutic ratio. Stereotactic, hypofractionated, pulsed-reduced dose-rate, and particle radiotherapy are re-irradiation techniques each uniquely suited for different clinical scenarios. Novel radiotherapy approaches, such as FLASH, represent promising advancements in radiotherapy for glioblastoma.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

Multimodality In Vivo Imaging of Perfusion and Glycolysis in a Rat Model of C6 Glioma

PURPOSE

Chemical exchange saturation transfer MRI using an infusion of glucose (glucoCEST) is sensitive to the distribution of glucose in vivo; however, whether glucoCEST is more related to perfusion or glycolysis is still debatable. We compared glucoCEST to computed tomography perfusion (CTP), [¹⁸F] fluorodeoxyglucose positron emission tomography (FDG-PET), and hyperpolarized [1-¹³C] pyruvate magnetic resonance spectroscopy imaging (MRSI) in a C6 rat model of glioma to determine if glucoCEST is more strongly correlated with measurements of perfusion or glycolysis.

METHODS

10⁶ C6 glioma cells were implanted in Wistar rat brains (n = 11). CTP (including blood volume, BV; blood flow, BF; and permeability surface area product, PS) and FDG-PET standardized uptake value (SUV) were acquired at 11 to 13 days post-surgery. GlucoCEST measurements (∆CEST) were acquired the following day on a 9.4 T MRI before and after an infusion of glucose solution. This was followed by MRSI on a 3.0 T MRI after the injection of hyperpolarized [1-¹³C] pyruvate to generate regional maps of the lactate:pyruvate ratio (Lac:Pyr). Pearson's correlations between glucoCEST, CTP, FDG-PET, and Lac:Pyr ratio were evaluated.

RESULTS

Tumors had significantly higher SUV, BV, and PS than the contralateral brain. Tumor ∆CEST was most strongly correlated with CTP measurements of BV (ρ = 0.74, P = 0.01) and PS (ρ = 0.55, P = 0.04). No significant correlation was found between glycolysis measurements of SUV or Lac:Pyr with tumor ∆CEST. PS significantly correlated with SUV (ρ = 0.58, P = 0.005) and Lac:Pyr (ρ = 0.75, P = 0.005). BV significantly correlated with Lac:Pyr (ρ = 0.57, P = 0.02), and BF significantly correlated with SUV (ρ = 0.49, P = 0.02).

CONCLUSION

This study determined that glucoCEST is more strongly correlated to measurements of perfusion than glycolysis. GlucoCEST measurements have additional confounds, such as sensitivity to changing pH, that merit additional investigation.

Prognostic Value of Dynamic Contrast-Enhanced MRI-Derived Pharmacokinetic Variables in Glioblastoma Patients: Analysis of Contrast-Enhancing Lesions and Non-Enhancing T2 High-Signal Intensity Lesions

OBJECTIVE

To evaluate pharmacokinetic variables from contrast-enhancing lesions (CELs) and non-enhancing T2 high signal intensity lesions (NE-T2HSILs) on dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for predicting progression-free survival (PFS) in glioblastoma (GBM) patients.

MATERIALS AND METHODS

Sixty-four GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. We analyzed the pharmacokinetic variables of the volume transfer constant (Ktrans) and volume fraction of extravascular extracellular space within the CEL and NE-T2HSIL of the entire tumor. Univariate and multivariate Cox regression analyses were performed using preoperative clinical characteristics, pharmacokinetic variables of DCE MR imaging, and postoperative molecular biomarkers to predict PFS.

RESULTS

The increased mean Ktrans of the CEL, increased 95th percentile Ktrans of the CELs, and absence of methylated O⁶-methylguanine-DNA methyltransferase promoter were relevant adverse variables for PFS in the univariate analysis (p = 0.041, p = 0.032, and p = 0.083, respectively). The Kaplan-Meier survival curves demonstrated that PFS was significantly shorter in patients with a mean Ktrans of the CEL > 0.068 and 95th percentile Ktrans of the CEL>0.223 (log-rank p = 0.038 and p = 0.041, respectively). However, only mean Ktrans of the CEL was significantly associated with PFS (p = 0.024; hazard ratio, 553.08; 95% confidence interval, 2.27-134756.74) in the multivariate Cox proportional hazard analysis. None of the pharmacokinetic variables from NE-T2HSILs were significantly related to PFS.

CONCLUSION

Among the pharmacokinetic variables extracted from CELs and NE-T2HSILs on preoperative DCE MR imaging, the mean Ktrans of CELs exhibits potential as a useful imaging predictor of PFS in GBM patients.

Developing a Pipeline for Multiparametric MRI-Guided Radiation Therapy: Initial Results from a Phase II Clinical Trial in Newly Diagnosed Glioblastoma

Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.

Prognostic Predictions for Patients with Glioblastoma after Standard Treatment: Application of Contrast Leakage Information from DSC-MRI within Nonenhancing FLAIR High-Signal-Intensity Lesions

BACKGROUND AND PURPOSE

Attempts have been made to quantify the microvascular leakiness of glioblastomas and use it as an imaging biomarker to predict the prognosis of the tumor. The purpose of our study was to evaluate whether the extraction fraction value from DSC-MR imaging within nonenhancing FLAIR hyperintense lesions was a better prognostic imaging biomarker than dynamic contrast-enhanced MR imaging parameters for patients with glioblastoma.

MATERIALS AND METHODS

A total of 102 patients with glioblastoma who received a preoperative dynamic contrast-enhanced MR imaging and DSC-MR imaging were included in this retrospective study. Patients were classified into the progression (n = 87) or nonprogression (n = 15) groups at 24 months after surgery. We extracted the means and 95th percentile values for the contrast leakage information parameters from both modalities within the nonenhancing FLAIR high-signal-intensity lesions.

RESULTS

The extraction fraction 95th percentile value was higher in the progression-free survival group of >24 months than at ≤24 months. The median progression-free survival of the group with an extraction fraction 95th percentile value of >13.32 was 17 months, whereas that of the group of ≤13.32 was 12 months. In addition, it was an independent predictor variable for progression-free survival in the patients regardless of their ages and genetic information.

CONCLUSIONS

The extraction fraction 95th percentile value was the only independent parameter for prognostic prediction in patients with glioblastoma among the contrast leakage information, which has no statistically significant correlations with the DCE-MR imaging parameters.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Integration of PET/MR Hybrid Imaging into Radiation Therapy Treatment

Hybrid PET/MR imaging is in early development for treatment planning. This article briefly reviews research and clinical applications of PET/MR imaging in radiation oncology. With improvements in workflow, more specific tracers, and fast and robust acquisition protocols, PET/MR imaging will play an increasingly important role in better target delineation for treatment planning and have clear advantages in the evaluation of tumor response and in a better understanding of tumor heterogeneity. With advances in treatment delivery and the potential of integrating PET/MR imaging with research on radiomics for radiation oncology, quantitative and physiologic information could lead to more precise and personalized RT.

Visual inspection of MR relative cerebral blood volume maps has limited value for distinguishing progression from pseudoprogression in glioblastoma multiforme patients

AIM

We examined whether visual interpretation of relative cerebral blood volume (rCBV) color maps made with dynamic susceptibility-weighted perfusion MRI can reliably distinguish progressive disease (PD) from pseudoprogression (PsPD) in glioblastoma patients during treatment with temozolomide chemoradiation.

MATERIALS & METHODS

Magnetic resonance (MR) perfusion-weighted images were evaluated based on visual inspection of rCBV maps. Sensitivity and specificity were calculated to assess if rCBV can reliably differentiate between PD and PsPD, during standard chemoradiation therapy.

RESULTS

Evaluation of dynamic susceptibility-weighted contrast-enhanced perfusion MRI by visual interpretation of rCBV maps did not differentiate PD from PsPD (sensitivity = 72%; specificity = 23%). Furthermore, the interpretation of the rCBV maps had no prognostic value regarding survival.

CONCLUSION

Qualitative rCBV-based dynamic susceptibility-weighted contrast-enhanced perfusion MRI does not reliably differentiate PD from PsPD, and is not prognostic for survival in glioblastoma multiforme patients during treatment with temozolomide chemoradiation.

MR-guided radiation therapy: transformative technology and its role in the central nervous system

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.

Automated Processing of Dynamic Contrast-Enhanced MRI: Correlation of Advanced Pharmacokinetic Metrics with Tumor Grade in Pediatric Brain Tumors

BACKGROUND AND PURPOSE

Pharmacokinetic parameters from dynamic contrast-enhanced MR imaging have proved useful for differentiating brain tumor grades in adults. In this study, we retrospectively reviewed dynamic contrast-enhanced perfusion data from children with newly diagnosed brain tumors and analyzed the pharmacokinetic parameters correlating with tumor grade.

MATERIALS AND METHODS

Dynamic contrast-enhanced MR imaging data from 38 patients were analyzed by using commercially available software. Subjects were categorized into 2 groups based on pathologic analyses consisting of low-grade (World Health Organization I and II) and high-grade (World Health Organization III and IV) tumors. Pharmacokinetic parameters were compared between the 2 groups by using linear regression models. For parameters that were statistically distinct between the 2 groups, sensitivity and specificity were also estimated.

RESULTS

Eighteen tumors were classified as low-grade, and 20, as high-grade. Transfer constant from the blood plasma into the extracellular extravascular space (K^trans), rate constant from extracellular extravascular space back into blood plasma (K_ep), and extracellular extravascular volume fraction (V_e) were all significantly correlated with tumor grade; high-grade tumors showed higher K^trans, higher K_ep, and lower V_e. Although all 3 parameters had high specificity (range, 82%-100%), K_ep had the highest specificity for both grades. Optimal sensitivity was achieved for V_e, with a combined sensitivity of 76% (compared with 71% for K^trans and K_ep).

CONCLUSIONS

Pharmacokinetic parameters derived from dynamic contrast-enhanced MR imaging can effectively discriminate low- and high-grade pediatric brain tumors.

Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging

OBJECTIVES

To identify candidate imaging biomarkers for early disease progression in glioblastoma multiforme (GBM) patients by analysis of dynamic contrast-enhanced (DCE) MR parameters of non-enhancing T2 high signal intensity (SI) lesions.

METHODS

Forty-nine GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. According to the Response Assessment in Neuro-Oncology criteria, patients were classified into progression (n = 21) or non-progression (n = 28) groups. We analysed the pharmacokinetic parameters of Ktrans, Ve and Vp within non-enhancing T2 high SI lesions of each tumour. The best percentiles of each parameter from cumulative histograms were identified by the area under the receiver operating characteristic curve (AUC) and were compared using multivariate stepwise logistic regression.

RESULTS

For the differentiation of early disease progression, the highest AUC values were found in the 99th percentile of Ktrans (AUC 0.954), the 97th percentile of Ve (AUC 0.815) and the 94th percentile of Vp (AUC 0.786) (all p < 0.05). The 99th percentile of Ktrans was the only significant independent variable from the multivariate stepwise logistic regression (p = 0.002).

CONCLUSIONS

We found that the Ktrans of non-enhancing T2 high SI lesions in GBM patients holds potential as a candidate prognostic marker in future prospective studies.

KEY POINTS

• DCE MR imaging provides candidate prognostic marker of GBM after standard treatment. • Cumulative histogram was applied to include entire non-enhancing T2 high SI lesions. • The 99th percentile value of Ktrans was the most likely potential biomarker.

Small increases in enhancement on MRI may predict survival post radiotherapy in patients with glioblastoma

To assess impact of volumetric changes in tumour volume post chemoradiotherapy in glioblastoma. Patients managed with chemoradiotherapy between 2008 and 2011 were included. Patients with incomplete MRI sets were excluded. Analyses were performed on post-operative MRI, and MRIs at 1 month (M+1), 3 months (M+3), 5 months (M+5), 7 months (M+7), and 12 months (M+12) post completion of RT. RANO definitions of response were used for all techniques. Modified RANO criteria and two volumetric analysis techniques were used. The two volumetric analysis techniques involved utility of the Eclipse treatment planning software to calculate the volume of delineated tissue: surgical cavity plus all surrounding enhancement (Volumetric) versus surrounding enhancement only (Rim). Retrospective analysis of 49 patients with median survival of 18.4 months. Using Volumetric analysis the difference in MS for patients who had a <5 % increase versus ≥5 % at M+3 was 23.1 versus 15.1 months (p = 0.006), and M+5 was 26.3 versus 15.1 months (p = 0.006). For patients who were classified as progressive disease using modified RANO criteria at M+1 and M+3 there was a difference in MS compared with those who were not (M+1: 13.1 vs. 19.4 months, p = 0.017, M+3: 13.2 vs. 20.1 months, p = 0.096). An increase in the volume of cavity and enhancement of ≥5 % at M+3 and M+5 post RT was associated with reduced survival, suggesting that increases in radiological abnormality of <25 % may predict survival.

Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression

BACKGROUND AND PURPOSE

MR imaging in neuro-oncology is challenging due to inherent ambiguities in proton signal behavior. Sodium-MR imaging may substantially contribute to the characterization of tumors because it reflects the functional status of the sodium-potassium pump and sodium channels.

MATERIALS AND METHODS

Sodium-MR imaging data of patients with treatment-naïve glioma WHO grades I-IV (n = 34; mean age, 51.29 ± 17.77 years) were acquired by using a 7T MR system. For acquisition of sodium-MR images, we applied density-adapted 3D radial projection reconstruction pulse sequences. Proton-MR imaging data were acquired by using a 3T whole-body system.

RESULTS

We demonstrated that the initial sodium signal of a treatment-naïve brain tumor is a significant predictor of isocitrate dehydrogenase (IDH) mutation status (P < .001). Moreover, independent of this correlation, the Cox proportional hazards model confirmed the sodium signal of treatment-naïve brain tumors as a predictor of progression (P = .003). Compared with the molecular signature of IDH mutation status, information criteria of model comparison revealed that the sodium signal is even superior to IDH in progression prediction. In addition, sodium-MR imaging provides a new approach to noninvasive tumor classification. The sodium signal of contrast-enhancing tumor portions facilitates differentiation among most glioma types (P < .001).

CONCLUSIONS

The information of sodium-MR imaging may help to classify neoplasias at an early stage, to reduce invasive tissue characterization such as stereotactic biopsy specimens, and overall to promote improved and individualized patient management in neuro-oncology by novel imaging signatures of brain tumors.

Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced MR in Tumor Parenchyma and Peritumoral Area for Distinction of Brain Tumors

Purpose

To quantitatively evaluate the diagnostic efficiency of parameters from diffusion and dynamic contrast-enhanced MR which based on tumor parenchyma (TP) and peritumoral (PT) area in classification of brain tumors.

Methods

45 patients (male: 23, female: 22; mean age: 46 y) were prospectively recruited and they underwent conventional, DCE-MR and DWI examination. With each tumor, 10–15 regions of interest (ROIs) were manually placed on TP and PT area. ADC and permeability parameters (K^trans, Ve, Kep and iAUC) were calculated and their diagnostic efficiency was assessed.

Results

In TP, all permeability parameters and ADC value could significantly discriminate Low- from High grade gliomas (HGG) (p<0.001); among theses parameters, Ve demonstrated the highest diagnostic power (iAUC: 0.79, cut-off point: 0.15); the most sensitive and specific index for gliomas grading were K^trans (84%) and Kep (89%). While, in PT area, only K^trans could help in gliomas grading (P = 0.009, cut-off point: 0.03 min^-1). Moreover, in TP, mean Ve and iAUC of primary central nervous system lymphoma (PCNSL) and metastases were significantly higher than that in HGG (p<0.003). Further, in PT area, mean K^trans (p≤0.004) could discriminate PCNSL from HGG and ADC (p≤0.003) could differentiate metastases with HGG.

Conclusions

Quantitative ADC and permeability parameters from Diffusion and DCE-MR in TP and PT area, especially DCE-MR, can aid in gliomas grading and brain tumors discrimination. Their combined application is strongly recommended in the differential diagnosis of these tumor entities.

Breast cancer redox heterogeneity detectable with chemical exchange saturation transfer (CEST) MRI

PURPOSE

Tissue redox state is an important mediator of various biological processes in health and diseases such as cancer. Previously, we discovered that the mitochondrial redox state of ex vivo tissues detected by redox scanning (an optical imaging method) revealed interesting tumor redox state heterogeneity that could differentiate tumor aggressiveness. Because the noninvasive chemical exchange saturation transfer (CEST) MRI can probe the proton transfer and generate contrasts from endogenous metabolites, we aim to investigate if the in vivo CEST contrast is sensitive to proton transfer of the redox reactions so as to reveal the tissue redox states in breast cancer animal models.

PROCEDURES

CEST MRI has been employed to characterize tumor metabolic heterogeneity and correlated with the redox states measured by the redox scanning in two human breast cancer mouse xenograft models, MDA-MB-231 and MCF-7. The possible biological mechanism on the correlation between the two imaging modalities was further investigated by phantom studies where the reductants and the oxidants of the representative redox reactions were measured.

RESULTS

The CEST contrast is found linearly correlated with NADH concentration and the NADH redox ratio with high statistical significance, where NADH is the reduced form of nicotinamide adenine dinucleotide. The phantom studies showed that the reductants of the redox reactions have more CEST contrast than the corresponding oxidants, indicating that higher CEST effect corresponds to the more reduced redox state.

CONCLUSIONS

This preliminary study suggests that CEST MRI, once calibrated, might provide a novel noninvasive imaging surrogate for the tissue redox state and a possible diagnostic biomarker for breast cancer in the clinic.

Advances in Magnetic Resonance and Positron Emission Tomography Imaging: Assessing Response in the Treatment of Low-Grade Glioma

Following combined-modality therapy for the treatment of low-grade gliomas, the assessment of treatment response and the evaluation of disease progression are uniformly challenging. In this article, we review existing response criteria, and discuss the limitations of conventional magnetic resonance imaging to distinguish between progression and treatment effect. We review the data on advanced imaging techniques including positron emission tomography and functional magnetic resonance imaging, which may enhance the interpretation of posttreatment changes, and enable the earlier assessment of the efficacy and toxicity of therapy in these patients with prolonged survival.

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

PURPOSE

To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy.

METHODS

Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. A DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes.

RESULTS

The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment.

CONCLUSIONS

The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.

Chemoirradiation for glioblastoma multiforme: the national cancer institute experience

Purpose

Standard treatment for glioblastoma (GBM) is surgery followed by radiation (RT) and temozolomide (TMZ). While there is variability in survival based on several established prognostic factors, the prognostic utility of other factors such as tumor size and location are not well established.

Experimental Design

The charts of ninety two patients with GBM treated with RT at the National Cancer Institute (NCI) between 1998 and 2012 were retrospectively reviewed. Most patients received RT with concurrent and adjuvant TMZ. Topographic locations were classified using preoperative imaging. Gross tumor volumes were contoured using treatment planning systems utilizing both pre-operative and post-operative MR imaging.

Results

At a median follow-up of 18.7 months, the median overall survival (OS) and progression-free survival (PFS) for all patients was 17.9 and 7.6 months. Patients with the smallest tumors had a median OS of 52.3 months compared to 16.3 months among patients with the largest tumors, P = 0.006. The patients who received bevacizumab after recurrence had a median OS of 23.3 months, compared to 16.3 months in patients who did not receive it, P = 0.0284. The median PFS and OS in patients with periventricular tumors was 5.7 and 17.5 months, versus 8.9 and 23.3 months in patients with non-periventricular tumors, P = 0.005.

Conclusions

Survival in our cohort was comparable to the outcome of the defining EORTC-NCIC trial establishing the use of RT+TMZ. This study also identifies several potential prognostic factors that may be useful in stratifying patients.

Measurements of tumor vascular leakiness using DCE in brain tumors: clinical applications

Various imaging techniques have been employed to evaluate blood-brain-barrier leakiness in brain tumors, as higher tumor vascular leakiness is known to be associated with higher grade and malignant potential of the tumor, and hence can help provide additional diagnostic and prognostic information. These imaging techniques range from routine post-contrast T1 -weighted images that highlight degree of contrast enhancement to absolute measurement of quantitative metrics of vascular leakiness employing complex pharmacokinetic modeling. The purpose of this article is to discuss the clinical applications of available imaging techniques, and in particular dynamic contrast-enhanced T1 -weighted MR imaging (DCE-MRI), to evaluate tumor vascular leakiness.

Predictors of long-term survival in patients with glioblastoma multiforme: advancements from the last quarter century

Over the last quarter century there has been significant progress toward identifying certain characteristics and patterns in GBM patients to predict survival times and outcomes. We sought to identify clinical predictors of survival in GBM patients from the past 24 years. We examined patient survival related to tumor locations, surgical treatment, postoperative course, radiotherapy, chemotherapy, patient age, GBM recurrence, imaging characteristics, serum, and molecular markers. We present predictors that may increase, decrease, or play no significant role in determining a GBM patient's long-term survival or affect the quality of life.

Prognostic vascular imaging biomarkers in high-grade gliomas: tumor permeability as an adjunct to blood volume estimates

RATIONALE AND OBJECTIVES

Despite recent advances in the treatment of high-grade gliomas, overall survival (OS) remains poor, which underlines the importance of searching for and determining prognostic imaging biomarkers. The purpose of our retrospective study was to correlate patient survival with relative cerebral blood volume (rCBV) and permeability surface area-product (PS) measured using perfusion computed tomography (PCT) in patients with high-grade gliomas.

METHODS

This study was composed of 54 patients with high-grade gliomas (World Health Organization [WHO] grade III, n = 14; WHO grade IV, n = 40) who underwent pretreatment PCT. Kaplan-Meier survival estimates were computed to describe OS for patients with high-versus-low PCT parameters, as well as grade III and IV gliomas.

RESULTS

Differences in OS between high and low rCBV, PS, and rCBV + PS were significant (P < .001) for all high-grade gliomas. After adjustment for WHO grade, rCBV (P = .041) and rCBV + PS (P = .013) estimates remained significant, whereas PS estimates were not (P = .214). PS estimates showed a statistically significant difference for OS in the grade III glioma group (P = .011), whereas for grade IV gliomas, rCBV estimates were statistically significant (P = .019). rCBV + PS was statistically significant for OS in both grade III (P = .001) and grade IV (P = .004) glioma groups.

CONCLUSIONS

Blood volume and permeability estimates measured using PCT can help predict survival in patients with high-grade gliomas. Patients with high PCT parameters showed worse OS compared to the patients with low PCT. Both rCBV and rCBV + PS remained statistically significant even after adjustment for WHO grade, suggesting these may be better predictors of OS than histological grade.

Physiological imaging-defined, response-driven subvolumes of a tumor

PURPOSE

To develop an image analysis framework to delineate the physiological imaging-defined subvolumes of a tumor in relating to treatment response and outcome.

METHODS AND MATERIALS

Our proposed approach delineates the subvolumes of a tumor based on its heterogeneous distributions of physiological imaging parameters. The method assigns each voxel a probabilistic membership function belonging to the physiological parameter classes defined in a sample of tumors, and then calculates the related subvolumes in each tumor. We applied our approach to regional cerebral blood volume (rCBV) and Gd-DTPA transfer constant (K(trans)) images of patients who had brain metastases and were treated by whole-brain radiation therapy (WBRT). A total of 45 lesions were included in the analysis. Changes in the rCBV (or K(trans))-defined subvolumes of the tumors from pre-RT to 2 weeks after the start of WBRT (2W) were evaluated for differentiation of responsive, stable, and progressive tumors using the Mann-Whitney U test. Performance of the newly developed metrics for predicting tumor response to WBRT was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

The percentage decrease in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was significantly greater in the group of responsive tumors than in the group of stable and progressive tumors (P<.007). The change in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was a predictor for post-RT response significantly better than change in the gross tumor volume observed during the same time interval (P=.012), suggesting that the physiological change occurs before the volumetric change. Also, K(trans) did not add significant discriminatory information for assessing response with respect to rCBV.

CONCLUSION

The physiological imaging-defined subvolumes of the tumors delineated by our method could be candidates for boost target, for which further development and evaluation is warranted.

Advanced techniques using contrast media in neuroimaging

This article presents an overview of advanced magnetic resonance (MR) imaging techniques using contrast media in neuroimaging, focusing on T2*-weighted dynamic susceptibility contrast MR imaging and T1-weighted dynamic contrast-enhanced MR imaging. Image acquisition and data processing methods and their clinical application in brain tumors, stroke, dementia, and multiple sclerosis are discussed.

An approach to identify, from DCE MRI, significant subvolumes of tumors related to outcomes in advanced head-and-neck cancer

PURPOSE

To develop and investigate a method to identify, from dynamic contrast enhanced (DCE) MRI, significant subvolumes of tumors related to treatment outcomes.

METHODS

A method, called global-initiated regularized local fuzzy clustering, was proposed to identify subvolumes of head-and-neck cancers (HNC) from heterogeneous distributions of tumor blood volume (BV) and blood flow (BF) for assessment of therapy response. BV and BF images, derived from DCE MRI, of 14 patients with advanced HNC were obtained before treatment and 2 weeks after the start of 7-week chemoradiation therapy (chemo-RT). The delineated subvolumes of tumors with low BV or BF before and during treatment were evaluated for their associations with local failure (LF). Receiver operating characteristic (ROC) analysis was used to assess performance of the method for prediction of local failure of HNC.

RESULTS

The sizes of the subvolumes of primary tumors with low BV, delineated by our method before and week 2 during treatment, were significantly greater in the patients with LF than with local control (LC) (p = 0.02 for pre-RT and 0.01 for week 2). While the total primary tumor volumes were reduced from baseline to week 2 during therapy to a similar extent for both the patients with LF and LC, the percentage decreases in the subvolumes of the primary tumors with low BV in the same time interval were significantly smaller for the patients with LF than those with LC (p < 0.05). ROC analysis shows that for any given sensitivity, the subvolume of the tumor with low BV week 2 during treatment has greater specificity for prediction of local failure than the pretreatment total tumor volume, the percentage change in the tumor volume week 2 during treatment, or the change in the averaged BV values of the entire tumor week 2 during therapy.

CONCLUSIONS

We developed a method to identify the significant subvolumes of primary tumors related to local failure. Large poorly perfused subvolumes of primary or nodal HNC before treatment and persisting during the early course of chemo-RT have the potential for prediction of local or regional failure, and could be candidates for local dose intensification.

A microRNA Link to Glioblastoma Heterogeneity

Glioblastomas (GBM) are one of the most malignant adult primary brain tumors. Through decades of research using various model systems and GBM patients, we have gained considerable insights into the mechanisms regulating GBM pathogenesis, but have mostly failed to significantly improve clinical outcome. For the most part GBM heterogeneity is responsible for this lack of progress. Here, we have discussed sources of cellular and microenvironmental heterogeneity in GBMs and their potential regulation through microRNA mediated mechanisms. We have focused on the role of individual microRNAs (miRNA) through their specific targets and miRNA mediated RNA-RNA interaction networks with the potential to influence various aspects of GBM heterogeneity including tumor neo-vascularization. We believe a better understanding of such mechanisms for regulation of GBM pathogenesis will be instrumental for future therapeutic options.

¹⁸F-Fluoromisonidazole positron emission tomography may differentiate glioblastoma multiforme from less malignant gliomas

PURPOSE

Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor and its prognosis is significantly poorer than those of less malignant gliomas. Pathologically, necrosis is one of the most important characteristics that differentiate GBM from lower grade gliomas; therefore, we hypothesized that (18)F fluoromisonidazole (FMISO), a radiotracer for hypoxia imaging, accumulates in GBM but not in lower grade gliomas. We aimed to evaluate the diagnostic value of FMISO positron emission tomography (PET) for the differential diagnosis of GBM from lower grade gliomas.

METHODS

This prospective study included 23 patients with pathologically confirmed gliomas. All of the patients underwent FMISO PET and (18)F-fluorodeoxyglucose (FDG) PET within a week. FMISO images were acquired 4 h after intravenous administration of 400 MBq of FMISO. Tracer uptake in the tumor was visually assessed. Lesion to normal tissue ratios and FMISO uptake volume were calculated.

RESULTS

Of the 23 glioma patients, 14 were diagnosed as having GBM (grade IV glioma in the 2007 WHO classification), and the others were diagnosed as having non-GBM (5 grade III and 4 grade II). In visual assessment, all GBM patients showed FMISO uptake in the tumor greater than that in the surrounding brain tissues, whereas all the non-GBM patients showed FMISO uptake in the tumor equal to that in the surrounding brain tissues (p ≤ 0.001). One GBM patient was excluded from FDG PET study because of hyperglycemia. All GBM patients and three of the nine (33%) non-GBM patients showed FDG uptake greater than or equal to that in the gray matter. The sensitivity and specificity for diagnosing GBM were 100 and 100% for FMISO, and 100 and 66% for FDG, respectively. The lesion to cerebellum ratio of FMISO uptake was higher in GBM patients (2.74 ± 0.60, range 1.71-3.81) than in non-GBM patients (1.22 ± 0.06, range 1.09-1.29, p ≤ 0.001) with no overlap between the groups. The lesion to gray matter ratio of FDG was also higher in GBM patients (1.46 ± 0.75, range 0.91-3.79) than in non-GBM patients (1.07 ± 0.62, range 0.66-2.95, p ≤ 0.05); however, overlap of the ranges did not allow clear differentiation between GBM and non-GBM. The uptake volume of FMISO was larger in GBM (27.18 ± 10.46%, range 14.02-46.67%) than in non-GBM (6.07 ± 2.50%, range 2.12-9.22%, p ≤ 0.001).

CONCLUSION

These preliminary data suggest that FMISO PET may distinguish GBM from lower grade gliomas.

Volumetric and MGMT parameters in glioblastoma patients: survival analysis

BACKGROUND

In this study several tumor-related volumes were assessed by means of a computer-based application and a survival analysis was conducted to evaluate the prognostic significance of pre- and postoperative volumetric data in patients harboring glioblastomas. In addition, MGMT (O6-methylguanine methyltransferase) related parameters were compared with those of volumetry in order to observe possible relevance of this molecule in tumor development.

METHODS

We prospectively analyzed 65 patients suffering from glioblastoma (GBM) who underwent radiotherapy with concomitant adjuvant temozolomide. For the purpose of volumetry T1 and T2-weighted magnetic resonance (MR) sequences were used, acquired both pre- and postoperatively (pre-radiochemotherapy). The volumes measured on preoperative MR images were necrosis, enhancing tumor and edema (including the tumor) and on postoperative ones, net-enhancing tumor. Age, sex, performance status (PS) and type of operation were also included in the multivariate analysis. MGMT was assessed for promoter methylation with Multiplex Ligation-dependent Probe Amplification (MLPA), for RNA expression with real time PCR, and for protein expression with immunohistochemistry in a total of 44 cases with available histologic material.

RESULTS

In the multivariate analysis a negative impact was shown for pre-radiochemotherapy net-enhancing tumor on the overall survival (OS) (p = 0.023) and for preoperative necrosis on progression-free survival (PFS) (p = 0.030). Furthermore, the multivariate analysis confirmed the importance of PS in PFS and OS of patients. MGMT promoter methylation was observed in 13/23 (43.5%) evaluable tumors; complete methylation was observed in 3/13 methylated tumors only. High rate of MGMT protein positivity (> 20% positive neoplastic nuclei) was inversely associated with pre-operative tumor necrosis (p = 0.021).

CONCLUSIONS

Our findings implicate that volumetric parameters may have a significant role in the prognosis of GBM patients. Furthermore, volumetry could help not only to improve the prediction of outcome but also the outcome itself by identifying patients at high risk of treatment failure and, thus, seek alternative treatment for these patients. In this small series, MGMT protein was associated with less aggressive tumor characteristics.

The promise of dynamic contrast-enhanced imaging in radiation therapy

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and computed tomography (CT) scanning are emerging as valuable tools to quantitatively map the spatial distribution of vascular parameters, such as perfusion, vascular permeability, blood volume, and mean transit time in tumors and normal organs. DCE MRI/CT have shown prognostic and predictive value for response of certain cancers to chemotherapy and radiation therapy. DCE MRI/CT offer the promise of early assessment of tumor response to radiation therapy, opening a window for adaptively optimizing radiation therapy based upon functional alterations that occur earlier than morphologic changes. DCE MRI/CT has also shown the potential of mapping dose responses in normal organs and tissue for evaluation of individual sensitivity to radiation, providing additional opportunities to minimize risks of radiation injury. The evidence for potentially applying DCE MRI and CT for selection and delineation of radiation boost targets is growing. The clinical use of DCE MRI and CT scanning as a biomarker or even a surrogate endpoint for radiation therapy assessment of tumor and normal organs must consider technical validation issues, including standardization, reproducibility, accuracy and robustness, and clinical validation of the sensitivity and specificity for each specific problem of interest. Although holding great promise, to date, DCE MRI and CT scanning have not been qualified as a surrogate endpoint for radiation therapy assessment or for treatment modification in any prospective phase III clinical trial for any tumor site.

Perfusion and permeability MR imaging of gliomas

Conventional contrast-enhanced MR imaging is the current standard technique for the diagnosis and treatment evaluation of gliomas and other brain neoplasms. However, this method is quite limited in its ability to characterize the complex biology of gliomas and so there is a need to develop more quantitative imaging methods. Perfusion and permeability MR imaging are two such techniques that have shown promise in this regard. This review will highlight the underlying principles, applications, and pitfalls of these evolving advanced MRI methods.

In vivo correlation of tumor blood volume and permeability with histologic and molecular angiogenic markers in gliomas

BACKGROUND AND PURPOSE

Tumor angiogenesis is very heterogeneous and in vivo correlation of perfusion imaging parameters with angiogenic markers can help in better understanding the role of perfusion imaging as an imaging biomarker. The purpose of this study was to correlate PCT parameters such as CBV and PS with histologic and molecular angiogenic markers in gliomas.

MATERIALS AND METHODS

Thirty-six image-guided biopsy specimens in 23 patients with treatment-naive gliomas underwent PCT examinations. We correlated MVD, MVCP, VEGFR-2 expression, tumor cellularity, and WHO grade of the image-guided biopsy specimens with the PCT parameters. Histologic sections were stained with hematoxylin-eosin, CD34, and VEGFR-2 and examined under a light microscope. These histologic and molecular angiogenic markers were correlated with perfusion parameters of the region of interest corresponding to the biopsy specimen. Pearson correlation coefficients and multiple regression analyses by using clustering methods were performed to assess these correlations.

RESULTS

CBV showed a significant positive correlation with MVD (r = 0.596, P < .001), whereas PS showed a significant positive correlation with MVCP (r = 0.546, P = .001). Both CBV (r = 0.373, P = .031) and PS (r = 0.452, P = .039) also showed a significant correlation with WHO grade. VEGFR-2 positive specimens showed higher PS and CBV; however, neither was statistically significant at the .05 level.

CONCLUSIONS

CBV showed a significant positive correlation with MVD, whereas PS showed a significant positive correlation with MVCP, suggesting that these 2 perfusion parameters represent different aspects of tumor vessels; hence, in vivo evaluation of these could be important in a better understanding of tumor angiogenesis.

Functional MRI for Radiotherapy of Gliomas

In this paper, we review the applications of functional magnetic resonance imaging (MRI) for target delineation and critical organ avoidance for brain radiotherapy. In this article we distinguish functional MRI from brain functional MRI (fMRI). Functional MRI includes magnetic resonance spectroscopic imaging (MRSI), perfusion MRI, diffusion tensor imaging (DTI) and brain fMRI. These functional MRI modalities can provide unique metabolic, pathological and physiological information that are not available in anatomic MRI and can potentially improve the treatment outcomes of brain tumors. For example, both choline (Cho) to N-acetylaspartate (NAA) and Cho to creatine (Cr) ratios from MRSI increase with increasing tumor malignancy and can be used to grade gliomas. Relative cerebral blood volume (rCBV) measurements from dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC MRI) are superior to conventional contrast-enhanced MRI in predicting tumor biology and may be even superior to pathologic assessment in predicting patient clinical outcomes. Brain fMRI can help identify and avoid functionally critical areas when constructing treatment plans for brain radiotherapy. In the past, functional MRI measurements have not been routinely used in a clinical arena due to the experimental nature of these imaging modalities. As these methods become more commonly used and effective image co-registration algorithms become available, integration of functional MRI into the treatment process of brain radiotherapy now appears to be clinically feasible, at least in major medical centers.

Emerging roles of brain-specific angiogenesis inhibitor 1

Brain-specific angiogenesis inhibitor 1 (BAI1) encodes a seven-transmembrane protein that belongs to the adhesion-GPCR family. Although BAI1 was named for the ability of its extracellular region to inhibit angiogenesis in tumor models, its function in physiological contexts was elusive and remained an orphan receptor until recently. BAI1 is now considered a phagocytic receptor that can recognize phosphatidylserine exposed on apoptotic cells. Moreover, BAI1 has been shown to function upstream of the signaling module comprised of ELMO/Dock180/Rac proteins, thereby facilitating the cytoskeletal reorganization necessary to mediate the phagocytic clearance of apoptotic cells. Here, we review the phylogeny, structure, associating proteins, as well as the known and proposed functions of BAI1.

MRI-based characterization of vascular disruption by 5,6-dimethylxanthenone-acetic acid in gliomas

The well-vascularized nature of gliomas has generated a lot of interest in antiangiogenic therapies. However, the potential of vascular disrupting agents (VDAs) against gliomas has not been investigated extensively. In this study, we examined the in vivo efficacy of the tumor-VDA 5,6-dimethylxanthenone-4-acetic acid (DMXAA) against gliomas. Contrast-enhanced magnetic resonance imaging (MRI) and diffusion-weighted MRI were used to characterize the vascular and cellular responses of GL261 and U87 gliomas to DMXAA treatment. Therapeutic efficacy was assessed by Kaplan-Meier survival analysis. Before VDA treatment, minimal enhancement was detected within the tumor in both models. Longitudinal relaxation rate (R1=1/T1) maps acquired 24 h after treatment showed marked extravasation and accumulation of the contrast agent in the tumor indicative of treatment-induced vascular disruption. Normalized change in relaxation rate (DeltaR1) values of the tumor showed a significant increase (P<0.01 GL261; P<0.05 U87) after therapy compared with baseline estimates. Mean apparent diffusion coefficient (ADC) values were significantly increased (P=0.015) 72 h after therapy in GL261 but not in U87 gliomas. Vascular disrupting agent therapy resulted in a significant (P<0.01) increase in median survival in both models evaluated. The results highlight the potential of VDAs against gliomas and the utility of MRI in the assessment of glioma response to VDA therapy.

Functional and metabolic magnetic resonance imaging and positron emission tomography for tumor volume definition in high-grade gliomas

Although the addition of concurrent and adjuvant temozolomide (TMZ) to standard-dose radiation (60 Gy) improves survival, the pattern of failure continues to be local. Conventional contrast enhanced T1-weighted and T2-weighted magnetic resonance imaging (MRI) used for radiation planning reflect anatomic rather than molecular or functional, properties of the tumor. Functional and metabolic MRI and positron emission tomography are able to detect metabolic and functional abnormalities beyond the tumor volume seen on conventional MRI, assess early response to treatment, and delineate the regions of high risks for failure in high-grade gliomas. This article focuses on the potential of these functional and metabolic imaging techniques to refine our clinical target volumes.

Complementary but distinct roles for MRI and 18F-fluoromisonidazole PET in the assessment of human glioblastomas

Glioblastoma multiforme is a primary brain tumor known for its rapid proliferation, diffuse invasion, and prominent neovasculature and necrosis. This study explores the in vivo link between these characteristics and hypoxia by comparing the relative spatial geometry of developing vasculature inferred from gadolinium-enhanced T1-weighted MRI (T1Gd), edematous tumor extent revealed on T2-weighted MRI (T2), and hypoxia assessed by 18F-fluoromisonidazole PET (18F-FMISO). Given the role of hypoxia in upregulating angiogenic factors, we hypothesized that the distribution of hypoxia seen on 18F-FMISO is correlated spatially and quantitatively with the amount of leaky neovasculature seen on T1Gd.

METHODS

A total of 24 patients with glioblastoma underwent T1Gd, T2, and 18F-FMISO-11 studies preceded surgical resection or biopsy, 7 followed surgery and preceded radiation therapy, and 11 followed radiation therapy. Abnormal regions seen on the MRI scan were segmented, including the necrotic center (T0), the region of abnormal blood-brain barrier associated with disrupted vasculature (T1Gd), and infiltrating tumor cells and edema (T2). The 18F-FMISO images were scaled to the blood 18F-FMISO activity to create tumor-to-blood ratio (T/B) images. The hypoxic volume (HV) was defined as the region with T/Bs greater than 1.2, and the maximum T/B (T/Bmax) was determined by the voxel with the greatest T/B value.

RESULTS

The HV generally occupied a region straddling the outer edge of the T1Gd abnormality and into the T2. A significant correlation between HV and the volume of the T1Gd abnormality that relied on the existence of a large outlier was observed. However, there was consistent correlation between surface areas of all MRI-defined regions and the surface area of the HV. The T/Bmax, typically located within the T1Gd region, was independent of the MRI-defined tumor size. Univariate survival analysis found the most significant predictors of survival to be HV, surface area of HV, surface area of T1Gd, and T/Bmax.

CONCLUSION

Hypoxia may drive the peripheral growth of glioblastomas. This conclusion supports the spatial link between the volumes and surface areas of the hypoxic and MRI regions; the magnitude of hypoxia, T/Bmax, remains independent of size.

Association of 11C-methionine PET uptake with site of failure after concurrent temozolomide and radiation for primary glioblastoma multiforme

PURPOSE

To determine whether increased uptake on 11C-methionine-PET (MET-PET) imaging obtained before radiation therapy and temozolomide is associated with the site of subsequent failure in newly diagnosed glioblastoma multiforme (GBM).

METHODS

Patients with primary GBM were treated on a prospective trial with dose- escalated radiation and concurrent temozolomide. As part of the study, MET-PET was obtained before treatment but was not used for target volume definition. Using automated image registration, we assessed whether the area of increased MET-PET activity (PET gross target volume [GTV]) was fully encompassed within the high-dose region and compared the patterns of failure for those with and without adequate high-dose coverage of the PET-GTV.

RESULTS

Twenty-six patients were evaluated with a median follow-up of 15 months. Nineteen of 26 had appreciable (>1 cm(3)) volumes of increased MET-PET activity before treatment. Five of 19 patients had PET-GTV that was not fully encompassed within the high-dose region, and all five patients had noncentral failures. Among the 14 patients with adequately covered PET-GTV, only two had noncentral treatment failures. Three of 14 patients had no evidence of recurrence more than 1 year after radiation therapy. Inadequate PET-GTV coverage was associated with increased risk of noncentral failures. (p < 0.01).

CONCLUSION

Pretreatment MET-PET appears to identify areas at highest risk for recurrence for patients with GBM. It would be reasonable to test a strategy of incorporating MET-PET into radiation treatment planning, particularly for identifying areas for conformal boost.