Advances in Magnetic Resonance Imaging and Positron Emission Tomography Imaging for Grading and Molecular Characterization of Glioma Caroline Chung, MD, FRCPC, CIP,* Ur Metser, MD,†,‡ and Cynthia Ménard, MD, FRCPC* In recent years, the management of glioma has evolved significantly, reflecting our better understanding of the underlying mechanisms of tumor development, tumor progression, and treatment response. Glioma grade, along with a number of underlying molecular and genetic biomarkers, has been recognized as an important prognostic and predictive factor that can help guide the management of patients. This article highlights advances in magnetic resonance imaging (MRI), including diffusion-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy, dynamic contrast-enhanced imaging, and perfusion MRI, as well as position emission tomography using various tracers including methyl-11C-L-methionine and O(2-18F-fluoroethyl)-L-tyrosine. Use of multiparametric imaging data has improved the diagnostic strength of imaging, introduced the potential to noninvasively interrogate underlying molecular features of low-grade glioma and to guide local therapies such as surgery and radiotherapy. Semin Radiat Oncol 25:164-171 C 2015 Elsevier Inc. All rights reserved.

Introduction

M

agnetic resonance imaging (MRI) is the imaging modality of choice to evaluate lesions in the brain, including low-grade gliomas (LGG). On conventional MRI, LGG typically present as lesions that are hyperintense on T2-weighted images, including fluid-attenuated inversion recovery (FLAIR) images, and hypointense on T1-weighted imaging with a lack of contrast enhancement. However, use of conventional MRI alone limits the accuracy of an imaging-based diagnosis. With recent advances in our understanding of prognostic and predictive factors of gliomas and within current paradigms

*Department of Radiation Oncology, University of Toronto/University Health Network-Princess Margaret Cancer Centre, Toronto, Ontario, Canada. †Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada. ‡Joint Department of Medical Imaging UHN, MSH and WCH, Toronto, Ontario, Canada. The authors declare no conflicts of interest. Address reprint requests to Caroline Chung, MD, FRCPC, CIP, Department of Radiation Oncology, Princess Margaret Cancer Centre, 610 University Ave, Rm 5-974, Toronto, Ontario, Canada M5G 2M9. E-mail: caroline. [email protected], [email protected]

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http://dx.doi.org/10.1016/j.semradonc.2015.02.002 1053-4296//& 2015 Elsevier Inc. All rights reserved.

of care, glioma grade and molecular genetic features frequently guide our management approach. In general, high-grade gliomas are treated aggressively with up-front surgical resection followed by radiotherapy with or without chemotherapy. In contrast, the management of LGG is often more conservative, even with an initial period of close observation, with serial imaging being considered in some cases. Common molecular and genetic features that are considered in the overall management approach for gliomas include 1p/19q deletion status and isocitrate dehydrogenase (IDH) mutation status. With advances in MRI and positron emission tomography (PET) imaging, there have been developments to better characterize tumors noninvasively with respect to grade, known molecular, and genetic factors such as 1p/19q deletion status and additional physiological features including tumor vascularity and metabolism.

Differentiation of Glioma Grade Glioma grade is directly associated with prognosis, and it is for this reason that grade dictates treatment. Although histologic confirmation is the gold standard for grading tumors, MRI is a

Advances in MRI and PET imaging for grading and molecular characterization of glioma particularly useful tool for diagnosing and for directing treatment of asymptomatic patients, particularly patients with tumors in eloquent locations of the brain. Furthermore, as gliomas may contain heterogenous regions of higher and lower grade, MRI provides information about the proportion and location of the higher grade components, and this may help guide diagnostic interventions such as biopsy and guide treatment including surgery and radiation. Identification of regions of tumor with contrast enhancement and necrosis on conventional MRI is traditionally used to distinguish high-grade gliomas from LGGs.1 However, studies have shown that approximately 20% of LGGs may show regions of contrast enhancement and that a third of nonenhancing gliomas are pathologically found to be high grade.2-4 Conversely, up to 45% of nonenhancing gliomas are found pathologically to be World Health Organization (WHO) grade III.5 Given the limitations of conventional MRI to distinguish low-grade vs high-grade gliomas (accuracy between 55% and 83%), advanced multiparametric magnetic resonance (MR) techniques have been explored including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), proton MR spectroscopy (MRS), and perfusion imaging.6-8 Many of these multiparametric MRI techniques interrogate the underlying pathophysiological features used to assign WHO grade including tumor cellularity, mitotic activity, microvascular hyperplasia, and presence of necrosis.

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Diffusion Tensor Imaging DTI measures the rate and the direction of water diffusion. A number of measures can be evaluated with DTI including the magnitude of diffusion (MD) and its isotropic (p) and anisotropic (q) components. An inverse relationship has been noted between the magnitude of diffusion and cellularity such that a lower magnitude of diffusion is suggestive of increased tumor cellularity.19 Tensor shape-based measures such as planar (CP) and spherical (CS) isotropy coefficients are also used for further tissue characterization. Finally, fractional anisotropy (FA) is a key measure of tissue microstructure that has been used to characterize different tumors. Studies have demonstrated that these DTI measures can be used to help distinguish high- vs LGGs. Smitha et al reported that mean values of p and MD (or L) are significantly different between low- and high-grade gliomas (P o 0.001), and on receiver operating characteristic analysis, the sensitivity was 93.9% and 91.8% and specificity was 53.3%, respectively.20 Although single measures on DTI, such as FA alone, have shown conflicting results, combinations of parameters may improve the performance of DTI. Ma et al21 reported that a combination of the 3 parameters, namely FA, CS, and CP, resulted in relatively high sensitivity (86%) and specificity (80%) for distinguishing low-grade from high-grade gliomas. Thus, there is a potential role for DTI indices such as FA, MD, CL, CP, and CS, likely used in combination, to improve brain tumor characterization and determine microstructural differences between tumor types and grades.

Diffusion-Weighted Imaging DWI measures the Brownian motion of water. Apparent diffusion coefficient (ADC), which reflects the mobility of water in tissue, is the most commonly used measure obtained from DWI. For the purposes of tumor grading, it was initially suggested that tumor cellularity is inversely related to the ADC such that areas of low or “minimum” ADC correspond to areas of high cellularity and higher tumor grade.9 Several studies, including that by Hilario et al,10 have reported that ADC values are significantly higher in LGGs than in high-grade gliomas.11,12 Other studies have reported correlations between ADC and features of more aggressive tumors including higher fluorodeoxyglucose (FDG)-PET uptake13 and shorter patient survival.14 However, the relationship between ADC and tumor grade is complicated by other histologic features that can affect the degree of water diffusivity beyond tumor cellularity including tumorassociated edema, hemorrhage, necrosis, and cystic or mucinous degeneration—features that are more commonly associated with higher grade tumors. The effects of compression within peritumoral tissue resulting from peritumoral edema can also result in lower ADC in regions of the tumor. Because of this complexity, various studies have reported mixed findings regarding the association between ADC and histologic tumor grade.15-18 Higano et al14 reported a significant correlation between minimum ADC and a measure of proliferation index (Ki–67) for a group of astrocytic tumors of varying grades, but this correlation was not seen in the subset of glioblastomas (GBM) tumors.

Dynamic Contrast-Enhanced MRI Dynamic contrast-enhanced MRI (DCE-MRI) is T1-weighted imaging that is acquired dynamically over several minutes with a high temporal resolution during intravenous injection of a volume of gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA). It is capable of measuring tumor perfusion, vessel permeability, and extravascular-extracellular space (EES) volume (ve). It also measures volume transfer coefficients between the plasma and EES (Ktrans) and the rate transfer constant between the EES and plasma (Kep). Estimations of these tumor vascular measures from DCE-MRI data require pharmacokinetic models that incorporate an arterial input function and other factors that make these models complex. Many methods for analyzing DCE data have been proposed, and there are efforts to standardize an approach for DCE-MRI acquisition and analysis to allow for comparison of results across studies and across institutions. As these measures can reflect the integrity of the blood-brain barrier and tumor vascular perfusion and permeability, these features may also reflect features that are associated with different tumor grades. Several studies have suggested that high-grade gliomas have greater vascular permeability, possibly reflecting local breakdown of the blood barrier, and therefore have higher Ktrans values than LGGs, although a consistent threshold value for distinguishing low- from high-grade gliomas has not yet been identified.22-24 Higher ve values have also been found in high-grade gliomas compared with LGGs.24 The practical ability of DCE-MRI to determine tumor grade is

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166 currently limited by the sensitivity of results to the specific image acquisition protocols, which can vary across vendors and across institutions; a matter which is further complicated by the significant differences in approaches to image analysis undertaken in the various studies.

MR Perfusion: Dynamic SusceptibilityWeighted Imaging and Arterial Spin Labeling Dynamic susceptibility-weighted perfusion (DSC) MRI is commonly used to estimate relative cerebral blood volume (rCBV) through dynamic measurement of the degradation of signal intensity over time associated with administration of a bolus of Gd-DTPA.25,26 The signal intensity on T2*-weighted images drops during the first pass of the bolus and then recovers as the agent recirculates. The change in T2* signal intensity over time is converted to the T2* relaxivity (ΔR2*), which is proportional to Gd-DTPA concentration at clinical doses of Gd-DTPA.25 Traditional calculations from this dynamic data attempt to estimate the elevated blood volume in a region of interest rCBV or in a tumor (relative tumor blood volume, rTBV) relative to normal white matter. Studies have shown rTBV measurements reflect the vascular proliferation in tumors.27,28 As vascular proliferation is a key feature used in the grading of gliomas, it would be expected that rTBV would correlate with tumor grade. Studies have confirmed that rTBV is higher in high-grade gliomas, and this measure can be useful in distinguishing low- from high-grade gliomas.3,26,29,30 Law et al evaluated 189 patients with both low- and high-grade gliomas with DSC and found that for patients with an rCBV o 1.75, low-grade tumors had a longer time to progression than high-grade gliomas, as expected. In contrast, tumors with an rCBV 4 1.75 progressed significantly faster, regardless of tumor grade.3 Arterial spin labeling (ASL) MRI is a perfusion imaging method that uses arterial blood water as an endogenous tracer to measure cerebral blood flow (CBF). Cebeci et al compared DSC measures including rCBV and rCBF with ASL measures including relative signal intensity (rSI), CBF, and relative CBF (ASL-rCBF) in 20 high-grade and 13 LGGs. Both measures on DSC (rCBV and rCBF) and on ASL (rSI, rCBF, and CBF) were significantly higher in high-grade gliomas than in LGGs (P o 0.001).31 There was a high correlation between rCBV measured on DSC and ASL-rCBF (r ¼ 0.81, P o 0.001).31 Additional studies have supported that ASL measures including rSI and rCBF are significantly different between low- and high-grade gliomas such that they may be useful in characterizing tumor grade noninvasively.32,33

MR Spectroscopy Proton MRS (1H-MRS) evaluates metabolites including Nacetylaspartate (NAA), choline (Cho) and creatine, lactate (if there is anaerobic metabolism), and lipids (with cellular breakdown secondary to necrosis). In terms of determining tumor grade, characteristic patterns of elevated Cho and decreased NAA have been reported. The presence of lipids and lactate has also been associated with higher tumor grade

and aggressiveness tumor behavior. However, the diagnostic accuracy of spectroscopy alone has been somewhat limited. A recent study by Di Constanzo et al34 reported a diagnostic accuracy of between 65% and 85%. The use of multiparametric imaging has the potential to significantly improve the diagnostic accuracy of gliomas. Fellah et al1 reported a combination of MRS, DWI, and perfusion imaging measures improves the sensitivity to 82% and specificity to 84% for discriminating between grade 2 and grade 3 oligodendroglial tumors.

PET Imaging With the growing array of PET tracers, PET imaging has the capability to interrogate an increasing number of physiological tumor properties, including glucose metabolism, proliferation, and hypoxia. Imaging data can be acquired dynamically or as single time point measures after specific time durations following tracer injection. Using 18F-FDG-PET, Mertens et al36 demonstrated that glucose metabolism of low-grade gliomas was lower than in normal brain whereas glucose metabolism was higher than normal brain in high-grade gliomas, as shown in other studies.35 In this particular study, the 18F-FDG uptake was measured at the conventional time interval of 60 þ 5 minutes after administration of 18F-FDG tracer and also at a delayed interval of 300 þ 5 minutes after tracer injection and found that differences in 18F-FDG uptake between low- and highgrade gliomas was more pronounced at the delayed interval (31%) compared with the conventional interval (2%) (P o 0.001).35,36 Although prior studies have demonstrated the limitations of FDG-PET for the evaluation of brain tumors owing to the high background physiological uptake of FDG in normal brain, this study exploited differences in uptake between normal brain, low- and high-grade tumors, which are potentially explained by variations in glucose efflux.36 A number of additional PET tracers have shown promise in differentiating tumor grade. Specifically, methyl-11C-L-methionine (11C-MET) has shown the ability to distinguish between low- and high-grade gliomas with high sensitivity and specificity.37,38 Unfortunately, the short 20-minute half-life of the 11 C isotope precludes its use at centers that lack access to an on-site cyclotron. In contrast, O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET), another amino acid tracer, has a much longer halflife of 109 minutes allowing for more widespread use. Using dynamic data from 18F-FET-PET, the combination of the early standardized uptake value with sum of frame-to-frame differences demonstrated an ability to distinguish low- and highgrade gliomas with high sensitivity (93%), specificity (100%), and accuracy (97%).37 Kinetic analysis of 18F-FET uptake has also demonstrated significant differences between glioma grade, with LGGs tending to have a steady increase in uptake without an identifiable peak and high-grade gliomas tending to have an early peak followed by a decrease in uptake.37 Recent studies have also shown that 18F-dihydroxyphenylalanine (18F-DOPA) has similar tumor uptake compared with 11CMET and thereby has good correlation with WHO tumor grade and proliferation, confirmed pathologically by

Advances in MRI and PET imaging for grading and molecular characterization of glioma Ki-67.39,40 However, a longer sustained uptake of 18F-FDOPA is observed in the normal striatum, which raises a challenge in using 18F-FDOPA in the evaluation of tumors located near the basal ganglia. A pilot study of 23 patients with glioma compared 18F-FDOPA (3,4-dihydroxy-6-F-18-fluoro-L-phenylalanine), 18F-FLT (30 -deoxy-30 -F-18-fluorothymidine), and 18F-FDG uptake in the tumor and found that 18FFDOPA was superior to 18F-FLT and FDG for identifying primary or recurrent LGG.41 Kinetic modeling of 18F-DOPA uptake has also been evaluated in establishing tumor grade, which showed high-grade tumors have a steep rise and descent in the 18F-FDOPA uptake curve whereas low-grade tumors have a more gradual declining curve that is similar to the cerebellum.42 Overall, the underlying physiology behind the variability in uptake of various tracers across the different histologies for LGG is not fully understood, and further studies are needed to interrogate the uptake kinetics of tumors in terms of their grade and the presence of specific tumor features such as ischemia and edema.

Multiparametric Imaging Although individual MRI imaging measures from DWI, DTI, perfusion or spectroscopy, and PET imaging have shown limited ability to differentiate tumor grade, efforts to combine the measures of multimodal and multiparametric imaging have led to improved results based on studies of histologic confirmation (Table). Fellah et al1 demonstrate that histologically confirmed grade 3 gliomas tend to have lower ADC (P ¼ 0.0008) and higher rCBV (P o 0.0001) and rCBF (P o 0.0001) compared with grade 2 gliomas. Similarly, Weber et al reported good agreement between higher grade tumor areas with decreased ADC and greater vascularity demonstrated by DSC (rCBV and rCBF), DCE (kep), ASL (rCBF), and areas of increased tumor proliferation demonstrated by areas of increased thymidine uptake using FLT PET.33 However, some studies have shown inconsistent relationships between the various multiparametric measurements and therefore have raised questions about our understanding of the underlying pathophysiology that is reflected in each of the specific imaging measures. For example, when Mills et al. evaluated 19 patients with GBM using ADC from DWI and ve from DCE-MRI, they found no correlation between ADC and ve using either median values for tumor volumes of interest or voxel-by-voxel analysis. Their hypothesis was that regions of low ADC reflect areas of high cellularity and that high cellularity would be inversely related to EES measured by ve. But the findings of this study suggest that these measures reflect aspects of the tumor microenvironment that are independent of each other.43 Rose et al demonstrated limited anatomical overlap between tumor regions of minimum ADC, thought to reflect higher cellularity, and areas of maximum 18 F-DOPA uptake, which reflects tumor infiltration and proliferation. Although these features were thought to likely coincide as high-grade tumors have greater cellularity, infiltration, and proliferation, these findings suggest that other factors may contribute to low ADC and high uptake of 18F-DOPA. For example, tumor ischemia and tissue compression or tumor

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necrosis may affect ADC measures.40 These discrepant results support the need for further investigation of the underlying pathophysiology reflected by each measure and emphasizes the value of using multiparametric imaging over any single functional or physiological imaging measure to improve the accuracy of tumor characterization.

Image-Guided Molecular Characterization Several molecular and genetic features have been found to be of strong prognostic value. These include 1p/19q loss of heterozygosity (LOH) and IDH mutation status. The 1p/19q status of gliomas has been proposed to predict for response to temozolomide. Therefore, accurate identification of tumors with 1p/19q LOH may be an important determinant for the treatment recommendations for patients with gliomas. The use of imaging characteristics to predict the underlying molecular signatures of gliomas introduces the potential to evaluate these tumor characteristics noninvasively and gather information about the distribution of these molecular signatures to appreciate the heterogeneity of these features within a tumor.44 Consistent imaging measures to detect 1p/19q deletion have not yet been identified. Studies have reported significantly higher rCBVmax in low-grade oligodendrogliomas with 1p/ 19q LOH, suggesting that 1p/19q codeletion is associated with increased vascularity in oligodendroglial tumors.1,45 Kapoor confirmed that rTBV was elevated only for LGGs with 1p19q codeletion. This study also showed that tumors that were either 1p19q LOH or 1p LOH had higher rTBV and greater VEGF, CD31, and CD105 expression based on real-time polymerase chain reaction analyses compared with tumors that were 1p19q intact or 19q LOH. However, for tumors with high EGFR expression, these vascular imaging and real-time polymerase chain reaction measures were elevated regardless of 1p19q deletion status.46 Using 1 H-MRS, Jenkinson et al47 showed that oligodendrogliomas with 1p/19q deletion have higher choline to creatinine (Cho:Cr) ratios than those with intact alleles, but the difference was not significant. By adding rCBV values to 1H-MRS measuring metabolite ratios (NAA:Cr, Cho:Cr, myo-inositol:Cr, and lipid-lactate:Cr), Chawla et al45 were able to discriminate the 1p/19q status between intact and lost alleles in oligodendrogliomas with a sensitivity of 82.6%, a specificity of 64.7%, and an accuracy of 72%. However, other investigators have not demonstrated similar results using multiparametric MR imaging to detect 1p/19q loss of alleles. Fellah et al reported no significant difference in DWI, perfusion weighted imaging (PWI), or MRS imaging measures between tumors with and without 1p/19q deletion. The study reported a 40% rate of tumor misclassification of 1p/19q status.1 These varying results may be due to differences in image acquisition, image analysis, and inclusion of particular tumor grades and tumor types (pure oligodendrogliomas, mixed gliomas, and variable EGFR status). Presence of IDH-1 and IDH-2 mutations results in a gain of function that leads to the accumulation of 2-hydroxyglutarate (2-HG) in gliomas. From resected tumors, excess 2-HG can be

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168 Table Summary of Imaging Measures That Distinguish Low- vs High-Grade Glioma MR/PET

Measure

Conventional MRI

Contrast enhancement Presence of necrosis

Diffusion imaging Diffusion-weighted imaging (DWI) Diffusion tensor imaging (DTI)

Vascular Imaging Dynamic contrast enhanced (DCE) Dynamic susceptibility weighted (DSC)

Metabolic imaging (MR spectroscopy)

Molecular imaging (PET)

Apparent diffusion coefficient (ADC) Fractional anisotropy (FA) Planar isotropy coefficient (CP) Spherical isotropy coefficient (CS) Volume transfer coefficient (Ktrans) Rate transfer constant between the extracellular extravascular space and the plasma (Kep) Volume fraction of the extravascular-extracellular space (ve) Relative cerebral blood volume (rCBV) Relative tumor blood volume (rTBV) Patterns of elevated: N-acetylaspartate (NAA) Choline (Cho) Creatine (Cre) Lactate (if there is anaerobic metabolism) Lipids (if there is necrosis) Static and dynamic uptake measures of various tracers: F-FDG 18F-FET 18 F-DOPA 11 C-MET 18 F-DOPA 18

detected using mass spectrometry. Recently, noninvasive in vivo detection of 2-HG has become possible using proton MRS. 48 As shown in Figure 1, Pope et al49 demonstrated preoperative 1H-MRS was able to detect 2-HG in 100% of tumors with IDH-1 mutation, and the in vivo 2-HG measures from MRS correlated with ex vivo chromatography-mass spectrometry measures of 2-HG (r2 ¼ 0.56; P o 0.0001).

Use of Advanced Imaging to Guide Surgery and Radiotherapy Although multiparametric imaging has improved the ability to grade gliomas, pathologic confirmation remains the gold standard. As gliomas are heterogeneous, imaging provides regional characterization and spatial information about the tumor heterogeneity that can help guide treatment. For example, multiparametric image guidance can noninvasively identify regions of tumor with more aggressive features that could be targeted for biopsy or for radiotherapy treatment planning.13,17,18 Whether for surgery or radiotherapy, identification of residual tumor is important for targeting treatment. Roder et al50 demonstrated that rCBV perfusion maps could be used to identify hot spots of both mean and maximum rCBV that were significantly higher in residual tumor compared with nontumor regions. Although, this was presented as a potential guide to help the surgeon to achieve a more complete resection, in situations where the residual tumor may be involving eloquent regions of the brain, these hot

spots may also be used to facilitate radiotherapy targeting. In this context, Castellano et al demonstrated the use of preoperative DTI tractography to predict the extent of resection that may be achievable in patients, which may affect the overall management approach. In this study, it was found that patients with intact white matter fiber tracts or fascicles on DTI had a higher likelihood of complete resection compared with patients with infiltrated or displaced fascicles.51 Functional mapping for patients with LGGs in suspected eloquent regions of the brain has also been suggested as a tool to improve delineation of true functional and nonfunctional areas to maximize tumor resection while maintaining function.52 In addition to multiparametric MRI, several groups have demonstrated the use of MET-PET in guiding surgery and radiation treatment planning of brain tumors.53,54 In highgrade gliomas, achieving complete resection of areas with high MET uptake has been associated with better survival.55 Uptake on MET-PET has been shown to distinguish tumor margins from peritumoral edema, even in areas of infiltrative, nonenhancing regions, with a sensitivity of 87% and a specificity of 89% compared with histologic confirmation.56 Studies have also shown differences between MET-PET and conventional MR-guided tumor delineation for radiotherapy.57,58 These studies suggest that MET-PET may improve target volume delineation for radiotherapy by identifying nonenhancing regions of tumor beyond the contrastenhanced MRI to maximize treatment efficacy while minimizing unnecessary toxicity by distinguishing tumor

Advances in MRI and PET imaging for grading and molecular characterization of glioma

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Fig. 1 Representative axial MR images and corresponding MR spectra of 2 anaplastic astrocytomas (WHO grade III). In panels (A) and (B), the 2 tumors, an IDH mutant tumor in (A) and wild-type tumor in (B), appear similar as hyperintense regions on fluid-attenuated inversion recovery (FLAIR) imaging. The voxels of interest for MR spectroscopic analysis were selected from the center of each solid tumor by 2 radiologists (demonstrated by the 2 boxes in the FLAIR images). The representative MR spectra of tumor (A) shown in (C) demonstrates extra peaks in the region of Glu/Gln/2-HG (centered at 2.25 ppm) that are increased in IDH mutant tumors vs the spectra of tumor (B) shown in (D), which lacks the extra peaks and is consistent with a wild-type tumor.49 (Color version of figure is available online.)

margins on MET-PET to avoid irradiating excessively large areas of MR FLAIR hyperintensity.57,58 Other PET tracers are also under investigation to complement conventional MR and computed tomography to guide

radiotherapy target delineation including 18F-DOPA,59 18 F-FET,60 and 11C-Cho.61 These investigations have demonstrated that metabolic imaging may provide increased confidence in delineating radiotherapy target volumes as well as

Fig. 2 Relationship between the agreement and discrepancy of MRI and PET for grades 2 (low grade), 3 (anaplastic), and 4 (GBM ¼ glioblastoma) gliomas.37

170 identifying aggressive tumor subregions that may benefit from higher radiation therapy doses in the form of a boost, further improving patient outcomes. Arbizu et al compared tumor volumes based on MRI and PET uptake in 23 patients with gliomas of varying tumor grade (10 GBM, 5 anaplastic, and 8 LGGs). They identified distinct patterns of discrepancy between the MRI- and PET-derived tumor volumes that were associated with the tumor grade. In the 10 GBM tumors, MET-PET showed areas of infiltrative tumor that extended beyond the volume defined by the contrast-enhanced MRI. In the 8 LGGs, the nonenhancing MRI-based tumor volumes showed infiltrating tumor that extended beyond the MET-PET uptake. Finally in the 3 patients with anaplastic grade 3 gliomas, the MRI-derived volume differed from the PET-derived volumes and did not completely coincide. This study raises the potential to use MET-PET and MRI to help delineate tumors for radiotherapy differently for tumors of different grades37 (Fig. 2).

Summary Management approaches for LGGs continue to evolve as our understanding of the underlying pathophysiology increases. Advances in imaging capabilities have introduced the potential to noninvasively evaluate some of the underlying tumor characteristics that may affect management including tumor grade, 1p/19q deletion status, and IDH-1 mutation status. Furthermore, multiparametric image guidance may aid targeting of local treatments including surgery and radiotherapy to increase treatment efficacy while minimizing treatment-related toxicities. Although there is great promise in these approaches, further research efforts will need to be invested in improving the correlation between imaging and histologic confirmation to enable meaningful interpretation of advanced imaging data.

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