Proton magnetic resonance spectroscopic evaluation of brain tumor metabolism

Proton Magnetic Resonance Spectroscopic Evaluation of Brain Tumor Metabolism Tracy Richmond McKnight Magnetic resonance imaging (MRI) is the neuroimaging method of choice for the noninvasive monitoring of patients with brain tumors due to the enormous amount of information it yields regarding the morphologic features of the lesion and surrounding parenchyma. Over the past decade, proton magnetic resonance spectroscopy (1H-MRS), which uses the same technology as MRI and can be performed during a routine clinical imaging examination, has been used to glean information about the metabolic status of the brain. Accurate interpretation of 1H-MRS data from individual patients requires an understanding of the various techniques for acquiring the data, the physiologic basis of the metabolic signatures obtained from different types of tumors, and the specificity of the technique. This review covers the basic physics of 1H-MRS, the spectral and physiological characteristics of the metabolites that are typically measured in various types of brain tumors, and the clinical utility of 1H-MRS with respect to diagnosis, therapeutic planning, and the assessment of response to treatment. Semin Oncol 31:605-617 © 2004 Elsevier Inc. All rights reserved.

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euroimaging is critical to the clinical management of patients with brain tumors. Although histopathologic grading of biopsies is the method of choice for diagnosing tumors, precise neuroimaging is required to guide the surgeon to the tumor location to retrieve the biopsy as well as to aid the pathologist in the tumor diagnosis. In cases where tumors arise in eloquent areas of the brain, the diagnosis is sometimes based entirely on the imaging characteristics of the tumor. The therapy of choice of many brain tumor types is surgical resection followed by radiation therapy and/or chemotherapy. Although the method of therapeutic intervention is determined by the diagnosis, the plan for administering therapy is guided by the location and spatial extent of the lesion observed on brain images. The need for neuroimaging methods that can assess physiologic function in addition to morphologic characteristics is becoming more apparent for lesions that are difficult to discriminate on conventional imaging, particularly because of the new focal therapeutic regimens being developed to treat the most malignant parts of the tumor while sparing normal brain. Examples include convection-enhanced delivery of chemothera-

Department of Radiology, University of California, San Francisco, CA. Supported by NCI K01 CA90244 and NCI P50 CA97297. Address reprint requests to Tracy Richmond McKnight, PhD, Center for Molecular and Functional Imaging, 185 Berry St, Ste 350, Department of Radiology, University of California, San Francisco, CA 94107. E-mail: [email protected]

0093-7754/04/$-see front matter © 2004 Elsevier Inc. All rights reserved. doi:10.1053/j.seminoncol.2004.07.003

peutic agents directly to the tumor and tumor bed,1,2 radiosurgical methods that deliver a single high-dose fraction to small lesions,3 and conformal/intensity-modulated radiotherapeutic methods used to administer differential doses to the gross tumor and its infiltration zone.4 After therapeutic intervention, neuroimaging is once again required to determine whether the tumor responded or progressed through therapy. Magnetic resonance imaging (MRI) is the neuroimaging method of choice for brain tumors due to the high resolution and signal-to-noise of the images and the marked contrast between anatomic structures in the brain that provides detailed information about tumor and peritumoral morphology. High signal on T2-weighted MRI signifies fluid regions within the brain parenchyma and is typically attributed to vasogenic edema associated with tumor infiltration. Bright lesions on T1-weighted MRI that appear after intravenous administration of a contrast agent such as gadolinium-DTPA designate regions where the blood-brain barrier has been compromised and the contrast agent has leaked into the interstitium. Even with such precise morphologic information, however, conventional MRI alone cannot always be used to distinguish between tumors with different prognoses or delineate the spatial extent of the tumor for planning therapy. In addition, the distinction between recurrent tumor and treatment-induced necrosis is not always clear in patients that have undergone therapy. Proton magnetic resonance spectroscopy (1H-MRS) uses 605

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606 the same basic principles as MRI, but it provides information about the underlying metabolism within the tumor. Several groups have studied the efficacy of using 1H-MRS as an additional clinical tool for managing patients with brain tumors.5-9 Over the past decade, many techniques have been developed for improved data acquisition,10-12 spectral localization,13 spectral quantification,14 and data interpretation.6,8,9,15 Accurate interpretation of 1H-MRS data from individual patients requires an understanding of the various techniques for acquiring the data, the physiologic basis of the different metabolic signatures obtained from different tumors, and the diagnostic specificity of the technique. This review will cover the basic physics of MRS, including differences between acquisition techniques that are often reported in the literature. Next, the spectral and physiological characteristics of the metabolites that are typically measured in various types of brain tumors will be reviewed. Lastly, the clinical utility of MRS for obtaining diagnostic information about brain tumors, planning therapeutic strategies for treatment, and discriminating recurrent tumor from the effects of therapy will be discussed.

Basic Principles of Magnetic Resonance Spectroscopy Magnetic Resonance Physics The MRI signal originates from the hydrogen protons comprising lipid and water molecules in the body. 1H-MRS is based on the same principles as MRI and is routinely used for clinical assessment of metabolic function in various organs such as brain, prostate,16-18 muscle,19-21 and breast.22-28 When a patient lies in the bore of an MRI magnet, the protons in the water molecules in his body rotate at an angle relative to the magnetic field (Bo), a property referred to as precession. To generate a signal from the precessing protons, an instantaneous radiofrequency (RF) pulse is used to “excite” the protons into a different quantum mechanical state. As the protons “relax” back to their original state, their precession generates a signal that can be detected with a receiver coil. The precession frequency for water protons in a 1.5Tesla (T) magnetic field is 63.8 MHz; thus, the spectrum acquired from a sample of pure water would be a single spike at that frequency. If another molecule containing protons in a configuration different from those of water (eg, lipid) is added to the sample, the resulting spectrum would have two spikes, one corresponding to each of the two types of molecules. By convention, the chemical compound corresponding to a given frequency is referred to by its position along the spectral axis or “chemical shift,” which is expressed in parts per million (ppm) and is independent of Bo.29 The main chemical shifts of interest at 1.5 T in spectra from normal human brain correspond to choline-containing compounds (Cho, 3.20 ppm), creatine ⫹ phosphocreatine (Cr/ PCr, 3.02 ppm), N-acetylaspartate (NAA, 2.02 ppm), myoinositol (myoI, 3.56 ppm), and glutamate (Glu) and glutamine (Gln), which are often referred in combination (Glx) and have two resonance frequency ranges (2.33 to 2.44

and 3.75 to 3.77).30,31 In diseased brain, the relative levels of the aforementioned metabolites are often altered, and resonance peaks corresponding to compounds such as alanine (Ala, 1.48 ppm), lactate (Lac, 1.33 ppm), and lipid (Lip, 0.9 and 1.3 ppm) may also be observed.7,32

Spectral Localization For patients with known or suspected brain tumors, 1H-MRS is typically used to determine the metabolic profile within a localized region of the brain that appears abnormal on MRI. The methods for localizing MRS signals result in either a single voxel or multiple voxels of spectra within a region excited with the RF pulse. Point-resolved spectroscopy (PRESS) and stimulated echo acquisition mode (STEAM) are the two most common techniques for single-voxel spectroscopy (SVS). In both cases, three orthogonal magnetic field gradients are used to select a single volume of interest (voxel) for RF excitation.29 The most common method for acquiring spectra in multiple voxels is chemical shift imaging (CSI), also referred to as magnetic resonance spectroscopic imaging (MRSI).33-35 In CSI, the excited volume is again defined with a PRESS or STEAM pulse sequence; however, the typical size of the excited region is 50 to 300 cc, in contrast to the 2- to 8-cc volumes used in SVS. Additional phase-encoding gradients are applied in two or three dimensions to subdivide the excited volume into subvolumes, or voxels. The individual voxels in CSI are typically on the order of 0.2 to 4 cc on a 1.5-T clinical scanner. An obvious difference between SVS and CSI is the difference in spatial coverage. Typically, two 8-cc single-voxel spectra are obtained during an SVS examination: one from the MRI lesion and one from contralateral normal-appearing brain for comparison. Even more spectra may be obtained if a single one cannot cover the entire MRI lesion. The multiple acquisitions increase the total time of the examination and may each have different signal characteristics depending on their location within the brain and the composition of tissue within the excited volume. Further, the choice of where to acquire the spectrum relative to the MRI lesion can have a profound effect on the resulting data content of the spectra. For this reason, brain tumor spectrum are typically obtained from the most solid-appearing region of the tumor to assess the most metabolically active tumor rather than tumor necrosis.36 In contrast to the single-voxel method, CSI results in an array of spectra that cover a much larger volume and allows for the simultaneous acquisition of spectra from the MRI lesion and contralateral brain. Thus the spectral signature from regions within and surrounding the MRI lesion can be assessed in a less subjective manner. Further, the position of the array of voxels within the excited region can be adjusted after the data are acquired using straightforward post-processing techniques.14 This is a powerful feature of CSI that allows one to interrogate specific areas within and surrounding the MRI lesion without having knowledge of the true spatial extent of the tumor at the

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Figure 1 Magnetic resonance spectra from normal brain: effect of TE. (A) TE ⫽ 272 ms, (B) TE ⫽ 144 ms, (C) TE ⫽ 65 ms, (D) TE ⫽ 40 ms. Note the emergence of short T2 metabolites (myoI, Cr/ PCr) as well as increased baseline noise at the shorter TEs. Figure courtesy of Daniel Vigneron.

time of acquisition. Using this feature, studies have shown that the most tumor-suggestive tumor patterns often occur outside of the contrast-enhancing lesion in newly diagnosed malignant glioma.4,37,38 An additional benefit of CSI is the smaller voxel size that allows one to probe the metabolic status of various regions within and around the MRI lesion in more detail. One other difference between SVS and CSI is the echo times (TE) that are commonly used with each method. The TE is basically the time delay between excitation and acquisition of the spectrum. After excitation, protons undergo two types of relaxation, longitudinal or T1 relaxation, which is typically exploited in contrast-enhanced MRI, and transverse or T2 relaxation. The size of the resonance peak associated with a given molecule is determined by the concentration of the molecule in the sample, the number of protons on the molecule, and the T2 relaxation time of the molecule. Thus, a sample with equal concentrations of three different molecules harboring the same number of protons, but with different T2 relaxation properties, will have three peaks of different sizes. Further, if a second spectrum is acquired from that same sample using a different TE, the relative sizes of the peaks will also change. Figure 1 illustrates the changes in the spectral signature from normal white matter that occur by simply changing the TE of the acquisition. Note the overall gain in signal when the TE is decreased from 272 ms (Fig 1A) to 144 ms (Fig 1B), including the detection of a second Cr/ PCr peak to the left of Cho. Further shortening of TE to 65 ms (Fig 1C) results in a change in the relative heights of Cho and Cr/PCr. At shorter TE (Fig 1D), the baseline of the spectrum becomes noisier and more difficult to define due to broad

spectral components contributed by macromolecules that have not had a chance to fully relax. Short TE (ⱕ50 ms) are used more often with SVS, whereas long TE (ⱖ135 ms) are commonly used with CSI. Thus, SVS is often used to detect compounds with short T2 relaxation times such as myoI and Gln/Glu, which are useful for diagnosing demyelinating diseases.39 Similarly, Ala, a compound that has been associated with meningiomas,30 is most readily detected with short echo sequences.

Brain Tumor Metabolites Choline The most robust MRS marker of brain tumors is an elevation in the resonance peak at 3.20 ppm,7,8,14,32,40-43 which is composed of peaks corresponding to phosphocholine (PC), glycerophosphocholine (GPC), and free Cho.44 As the individual peak components cannot be resolved in spectra obtained in vivo, the collective signal is typically referred to as the Cho peak. The increase in Cho can be observed with both short TE (Fig 2A and B) and long TE (Fig 3) spectra. However, in short TE spectra from tumors with a substantial lipid component, the Cho peak is less observable because of the increased dynamic range of the spectral data (Fig 2C). The Cho compounds are part of the normal phospholipid machinery that maintains the integrity of the cell membrane and the associated biochemical functions.44,45 Levels of PC and GPC increase during cell membrane synthesis and degradation, respectively.44,46 Cho intermediates that are formed during the phospholipid metabolic

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Figure 2 Short TE (TE ⫽ 30 ms) single-voxel spectra acquired with STEAM from three patients with (A) astrocytoma grade II, (B)meningioma, and (C) glioblastoma multiforme. Figure courtesy of Franklyn Howe.

events also contribute to the in vivo Cho signal. Thus, Cho is thought to be a local measure of cell density and membrane turnover, both of which are increased in tumors relative to normal brain. Several groups have sought to verify this presumed relationship by comparing the size of the Cho peak with the cellularity and/or proliferation rate of tissue samples collected from the tumor.37,47-52 Shino et al report a linear correlation (P ⬍ .01) between the ratio of Cho:Cr and the MIB-1 proliferation index in meningioma.52 For glioma, however, the reports have been more variable. For example, Barbarella et al53 reported a correlation between the ratio of Cho:Cr and the Ki-67 proliferation index, while two other groups47,50 found no significant relationship between the normalized Cho signal and the proliferative rate. Such variable results may arise from the different Cho parameters used in each study (eg, Cho:Cr v Cho:normal Cho), the different TE used, and variable accuracy in colocalizing the magnetic resonance spectrum with the brain regions from which biopsies were retrieved. A more consistent finding has been the correlation between Cho and cell density.50,54 The strength of the association imparts a reduced specificity on the Cho peak as a parameter for distinguishing neoplastic processes from other

neurologic abnormalities that recruit inflammatory cells.39,55-57 The influence of cell density on the size of the Cho peak is evident in spectra obtained from heterogeneous tumors such as glioblastoma multiforme, where Cho levels can vary widely presumably because of variable necrotic fractions throughout the tumor.6,49,58

Creatine/Phosphocreatine The 1H-MRS peak observed at 3.02 ppm in vivo is comprised of both Cr and PCr methyl resonances and is typically referred to as the total creatine (tCr) peak. Although the T2 relaxation of tCr peak is sufficiently long for it to be observed in both short and long TE spectra, it is shorter than the T2 of the nearby total Cho peak (3.20 ppm). The importance of this fact is illustrated in Fig 1, which shows the ratio of Cho:tCr in normal white matter is greater than 1 at short TE (Fig 1A and B) and less than 1 at longer TE (Fig 1C and D). Reduction in tCr below normal levels has been reported as a feature of high-grade gliomas,7,9,59-62 metastases,9,60,63 and meningiomas.32,62-68 The observed decrease in tCr is thought to be related to the increased metabolic rate of the tumor, but the specific biochemical mechanisms leading to the 1H-MRS– observable changes are not well understood. Several groups

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Figure 3 Example of long TE (TE ⫽ 144 ms) PRESS spectra. (A) T2-weighted image and single-voxel spectrum from normal appearing white matter of a patient with a low-grade glioma. (B) Spectrum from the lesion of the same patient. Note the increase in the Cho:Cr and Cho:NAA in the tumor spectrum. Figure courtesy of Daniel Vigneron.

reported an inverse relationship between tCr and astrocytoma grade.9,60,68 However, this finding is not consistent, particularly when both astrocytic and oligodendroglial tumors are included in the study.69,70 This may be because the tCr in high-grade and low-grade oligodendrogliomas does not differ as much as in astrocytomas, which is supported by a study by Rijpkema et al.71 Also, it can be difficult to adequately

resolve the tCr peak from the nearby Cho resonance in poorly shimmed spectra, thereby preventing accurate quantification of tCr. When meningiomas are included in studies seeking to classify tumor spectra, it is often reported that the tCr is significantly lower than in grade II and III astrocytic tumors.9,32,42,43,62,66,67 With respect to normal brain, in vivo65,68,72 and ex vivo72,73 1H-MRS spectra from meningio-

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Figure 4 Contrast-enhanced T1-weighted image and long TE (TE ⫽ 144 ms) single-voxel spectrum acquired with PRESS from a patient with high-grade glioma. Note inverted lactate doublet at 1.3 ppm. Figure courtesy of Daniel Vigneron.

mas are often characterized as having markedly reduced or absent tCr peak (Fig 2B).

N-Acetylaspartate The prominent peak at 2.0 ppm in Fig 3A corresponds to the neurotransmitter NAA, which primarily resides in neurons74,75 and is typically used as a spectroscopic indicator of normal neuronal function. The NAA peak is dramatically reduced in brain tumors,7,41,61,69,70,76 multiple sclerosis,39,77-79 Alzheimer’s disease,80-82 and other neuropathologies,56,83,84 reflecting the displacement of normal neurons with neoplastic and/or inflammatory cells. Figure 3B illustrates the NAA reduction in a low-grade glioma. In studies of patients with histologically proven brain tumors, the level of NAA has been shown to have some utility for distinguishing tumor from nontumor either as a standalone MRS marker or in conjunction with Cho.6 However, the disruption of neuronal tracts from surgery (unpublished observations), transient neuronal dysfunction after radiotherapy,41,85 and compromised neuronal function in normalappearing brain regions of patients with demyelinating diseases86 can all result in significant reductions in NAA. For this reason, one must proceed with caution when attempting to use the NAA level to define the spatial extent of the tumor or to distinguish tumor from other neurologic abnormalities.

Lactate Accurate measurement of Lac in short TE spectra is challenging because of the lipid resonance at 1.31 ppm, which is often large in high-grade brain tumors and can obscure the Lac peak at 1.33 ppm (Fig 2C). In magnetic resonance spectra collected with a long TE, the Lac doublet peak is inverted below the spectral baseline (Fig 4). For this reason, a long TE

spectrum is typically required to determine whether Lac is elevated.60,62 New pulse sequences that exploit the phase cycling phenomenon of coupled resonances have recently been developed to improve the quantification of Lac.87 Figure 5 is an example of Lac-edited spectra that were generated from two separate acquisitions, one in which the Lac peak is inverted and a second with different excitation RF pulses that cause the Lac peak to be upright. Addition of the two sets of spectra shows the contributions from Cho, tCr, NAA, and Lip (Fig 5A), while subtraction generates spectra showing Lac only (Fig 5B). Lac is thought to be an indicator of altered metabolism in brain tumors. Glucose metabolism is the sole mechanism by which the brain generates energy in the form of adenosine triphosphate (ATP). Unlike normal brain, which utilizes oxidative phosphorylation during glycolysis to convert pyruvate into 36 mol of ATP, brain tumors use the less efficient process of aerobic glycolysis that converts pyruvate into Lac ultimately resulting in 2 mol of ATP.88 This Lac-producing pathway is typically reserved for rapid energy production in poorly oxygenated conditions in other tissues such as skeletal muscle and is thus referred to as “anaerobic metabolism.” However, brain tumors utilize this pathway constitutively and, therefore, produce Lac independent of the availability of oxygen.88,89 Thus, Lac levels in brain tumors reflect the availability of glucose as well as the oxygenation status. The significance of Lac in tumor spectra with respect to diagnosis61,62,90,91 and predicting response to therapy5,92 is currently under investigation in several laboratories. The concentration of Lac in normal brain is too low to be detected in vivo with 1H-MRS. However, high-grade tumors such as glioblastoma multiforme and metastases often exhibit observable Lac resonances.60,62,63 The elevation in Lac may be

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Figure 5 Lactate-edited three-dimensional CSI data from a patient with an untreated anaplastic oligodendroglioma. Spectra were acquired with an echo time of 144 ms. Red box designates spectra coinciding with the MRI lesion. (A) Summed spectrum showing elevated Cho, and decreased Cr and NAA. (B) Difference spectrum showing elevated lactate doublet in the lesion.

due to the increased metabolic rate of these tumors, as well as to the reduced clearance of Lac in the necrotic regions that are also characteristic of these tumors.63 Elevated Lac can also occur in lower grade gliomas such as the grade III oligodendroma shown in Fig 57,62,70 as well as meningiomas,62 although not as readily as the more aggressive lesions.

Lipid The methyl (0.9 ppm) and methylene (1.3 ppm) Lip resonances are typically elevated in high-grade astrocytomas and metastases.7,15,41,58,60,62,93 Figure 6 shows that the lipid peaks can occur within the necrotic core of the tumor as well as in the contrast-enhancing rim. A recent study of grade III and grade IV astrocytomas provides evidence that the methylene resonance may even be an indicator of malignant transformation of astrocytoma.94 Murphy et al showed that the methylene resonance was significantly higher in the high-grade tumors and, further, that there was a trend toward increased Lip in patients with tumors originally diagnosed as grade II but with clinical and radiologic evidence of malignant transformation.

The biological basis of the increased Lip is presumed to be the necrosis that is a hallmark of high-grade astrocytoma. Recent studies have shown that the Lip resonance observed in magnetic resonance spectra is due to mobile Lip residing in intracellular vesicles or extracellular Lip droplets. Such mobile forms of Lip may be produced during changes in cellular proliferation that occur prior to the onset of necrosis95 or products of apoptotic processes induced by a chemotherapeutic agent.96

Glutamate/Glutamine Fueled by the recent availability of higher-field (3.0 T) clinical magnets, there has been an increased interest in the origin of the peaks at 2.35 ppm and 3.76 ppm corresponding to Glx. At 1.5 T, the current field strength of most clinical magnets, Glx resonances are most easily detected with short TE sequences but are difficult to quantify due to the characteristic rolling baseline of short TE spectra (Fig 2A and B). Despite this difficulty, several studies have reported elevated Glx in meningiomas relative to normal brain and astrocytomas.9,65,67 A recent study by Rijpkema et al, which compared

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Figure 6 Three-dimensional CSI data from a patient with a glioblastoma multiforme. The red box designates the contrast-enhancing MRI lesion. The red stars indicate tumor-suggestive spectra outside of the contrast-enhancing lesion.

the proton MRS profiles of patients with astrocytoma and oligodendroglioma, revealed an elevated Glx peak as characteristic for oligodendroglial tumors.71 Changes in Glx production are thought to reflect alterations in the tumor metabolic pathway,64,97 but a more specific source of the increased in vivo Glx peak has not been described.

Myo-inositol The peak originating at 3.56 ppm in in vivo magnetic resonance spectra is predominately due to myoI, although glycine (Gly) also resonates in the same region leading to the alternate shorthand terms of myoIG or mIG that are often used in the literature. The rapid T2 relaxation of myoI requires a short TE MRS sequence for detection (Figs 1D and 2A). MyoI is typically increased in glial tumors relative to normal brain62,98 and is generally higher in low-grade astrocytomas than high-grade gliomas or metastases.9,72,99,100 Rijpkema et al reported a similar trend in low-grade versus high-grade oligodendroglioma, although the difference did not reach statistical significance.71 The group further showed that there was no difference in the myoI levels in astrocytomas and oligodendrogliomas. In contrast to the patterns observed in gliomas, meningiomas most often have normal or decreased myoI relative to normal brain.9,42,62 The source of the myoI observed in magnetic resonance spectra from lowgrade gliomas is not clear, but it is thought to be an intermediate of phospholipid metabolism and primarily located in glial cells.30,62,100

Alanine Ala resonates at 1.47 ppm, as shown in the short TE spectrum in Fig 2B, but it is best detected as an inverted doublet in long TE spectra. It is more often observed in spectra from meningiomas than any other brain tumors.9,62,65,93 Studies have postulated an alternate metabolic pathway in meningioma

that produces Ala as an end-product, which may explain why it is an exclusive feature of meningioma spectra.62,67

Clinical Utility of MRS for Managing Patients With Brain Tumors Noninvasive Diagnosis of Glial Tumors The ability to use MRSI data to predict the histologic grade of infiltrative brain tumors is a subject of considerable controversy in the literature. Early single-voxel studies indicated that increasing Cho and Lac/Lip in the tumor spectra correlated with increasing histologic grade.32,63,70,76,101,102 Ex vivo MRS studies of chemical extracts from brain tumor biopsies also showed that higher grade tumors exhibited higher Cho103,104 and Lip levels105 and reported increases in other metabolites such as Ala and Gly with increasing grade.73 More recent in vivo studies have reported the ability to go beyond the observed associations and actually discriminate between populations of spectra from low- and high-grade gliomas using the relative sizes of three to four spectral peaks40,61,106 or sophisticated multivariate analyses that incorporate the entire spectral pattern.15,107 In addition to Cho, Cr, NAA, and Lac/Lip, short TE single-voxel spectroscopy studies have also revealed that other metabolites such as myoI100 and Gly15 may correlate with the degree of malignancy. Studies using multivoxel MRSI have also shown significant differences between populations of spectra from low- and high-grade brain tumors.6,8,69 In a recent study, we reported the ratio of Cho:NAA within the MRI lesions of grade III gliomas relative to control voxels in normal-appearing brain regions to be significantly higher than that of grade II, although there was some overlap between the data from the two groups.6 Furuya et al69 reported that the percent ratios of the Cho and the NAA peak areas, respectively, to the total

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spectral area were better for distinguishing tumor grade than the more commonly used ratio of Cho to normal Cho. Even in the face of such encouraging results, it is still not possible to definitively predict the histologic grade using the MRS pattern alone.7,9,98,108,109 There are several reasons for the apparent disparity between the above findings and the actual utility of MRS for grading tumors. First of all, the definition of “high-grade” and “low-grade” tumors varied or was omitted completely40 in the aforementioned studies. For example, grade III tumors were grouped with the grade II tumors in some cases103-105 and other times grouped with grade IV.15,59,76 Similarly, oligodendrogliomas were sometimes combined with astrocytomas15,59,69 or considered as an independent group.103,110 Studies have shown that grade III astrocytomas6 and oligodendrogliomas of all grades103 often have higher Cho levels than grade IV astrocytomas. Thus, the grouping may significantly affect the analysis of the data. Another reason for the disparity is that the studies typically report the ability to classify a group of spectra into several populations corresponding to various types as well as grades of brain tumors. The methods that have been most successful at distinguishing tumor grade generally use a training set of MRS patterns from histologically confirmed tumor to prime the classification scheme. The scheme must be able to classify spectral patterns that may vary due to heterogeneity within the lesion as well as differences in data acquisition and analysis.110 Thus, the training data set used can have a profound effect on the specificity of the scheme if it is not generated in a systematic manner and/or does not incorporate sufficient examples of spectra from each grade of tumor. The study by Preul et al8 that used linear discriminant analysis with “leaveone-out” to classify tumor spectra with 99% accuracy is the best example to date of using MRS to retrospectively differentiate between the three grades of astrocytomas. However, there has been no study that has shown the ability to prospectively predict tumor grade, on a case-by-case basis, using the MRS pattern alone.

Therapeutic Planning for Gliomas: Utility of MRS for Identifying Tumor and Predicting Response to Therapy Patients with malignant glioma are treated with surgical resection followed by a combination of chemotherapy and radiotherapy. The blood-brain barrier poses a significant obstacle for traditional chemotherapeutic interventions. Because of this, novel radiotherapy methods such as radiosurgery boost and intensity-modulated radiation therapy, also referred to as “dose painting” techniques, that preferentially deliver high doses to specific parts of the tumor are rapidly becoming part of the clinical arsenal for treating brain tumors.4,5 The common method for planning the radiation dose is to target a region containing the contrast-enhancing lesion on T1-weighted MRI and an institutionally varying margin of 1 to 4 cm to receive the highest dose, typically 60 Gy.111,112 The hyperintense lesion on T2-weighted MRI may also be targeted for a lower, but therapeutic, dose with the

613 hopes of treating microscopic tumor infiltration at the leading edges of the tumor.113,114 Nelson et al have shown in several studies that MRS patterns suggestive of tumor can be found outside of the borders of contrast-enhancement in high-grade glioma.4-6,38,108,115 In all of the studies, the relative levels of Cho and NAA were the primary metabolic parameters that were used to predict tumor presence, although the ratios of Cho:tCr and Lac/Lip levels were also evaluated. One of the most impressive findings regarding the predictive capability of 1H-MRS was reported by Graves et al in a study that compared the spatial relationship between regions with elevated Cho:NAA ratios derived from pretreatment threedimensional MRSI with the actual dose distribution for patients who received gamma-knife radiosurgery for recurrent highgrade glioma.38 The authors showed a 60-week difference in survival for patients whose metabolic abnormality was included within the high-dose region compared with patients that had voxels with elevated Cho:NAA ratios outside of the gammaknife target. Armed with these findings as well as data from histologic correlation studies from our laboratory demonstrating a strong relationship between the relative levels of Cho and NAA and tumor presence,37,116 we developed a Cho-to-NAA index (CNI) that assigns a value to the probability of tumor presence based on the difference in the relationship between Cho and NAA in a given voxel versus that of a set of control voxels from the same patient.6 In a study correlating the CNI with histopathology of biopsies taken from untreated tumors, McKnight et al report the ability to discriminate tumor from nontumor regions with 90% sensitivity and 86% specificity using a threshold CNI of 2.5.108 Further, 36% to 44% of the T2hyperintense region beyond the contrast-enhancing MRI lesion in the 42 patients with grades III and IV gliomas, respectively, had CNIs ⱖ 2.5.108 Patterns of recurrence analyses following conventional radiotherapy with 60 Gy have shown that about 80% of relapses occur within a 2-cm margin from the original tumor location.112,117 Taken together, these results suggest that restricting the dose to 60 Gy and targeting the contrast enhancement enlarged by uniform margin may not sufficiently treat metabolically active regions of high-grade glioma. Pirzkall et al explored this idea further in two different studies of how the incorporation of MRS information would impact the delineation of target volumes for low-grade118 and high-grade4 gliomas. For high-grade gliomas, they found that even when the more stringent criteria of CNI ⱖ 3.0 was added to the volume of contrast enhancement in order to define the target volume, the latter would be two- to threefold larger than that of the contrastenhancing volume alone.4 On the other hand, in low-grade gliomas, the region with CNI greater than 2.0 was on average half the volume of the T2-hyperintense lesion, the classical target for this tumor entity.118 Both high-grade and low-grade tumors exhibited some extension of the metabolic abnormality beyond the borders of the MRI lesion preferably following white matter tracts, although the extension was most pronounced in highgrade lesions. As a result, both reports questioned the definition of uniform margins for target definition and suggested the incorporation of physiologic imaging studies, such as MRSI, not only to custom-shape the target borders and therefore limit radiation exposure to surrounding unaffected brain tissue, but

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614 also to prescribe differential doses according to the tumor heterogeneity. Recent studies by Li et al investigating the distributions of the anatomic and metabolic abnormalities in gliomas of all grades showed that the volume of contrast-enhancement was correlated with the volume of elevated lactate/lipid and inversely correlated with the volume of relative tCr:NAA in glioblastoma multiforme.58 These results were interpreted as the contrast-enhancing region representing hypermetabolic tissue that has been shown to exhibit reductions in Cr:NAA66 and elevations in Lac119 in previous studies. If true, then it stands to reason that subregions within the contrast-enhancing lesion exhibiting high Lac and low tCr should also be targeted for administration of the highest radiation doses. This idea is supported by results from a study by Tarnawski et al that showed these patients with malignant glioma having a Lac:NAA ratio greater than 2.0 prior to radiotherapy had a shorter survival than those who did not.92 These findings show that the metabolic and anatomic targets are indeed different, which suggests that the outcome for patients treated with a regimen that includes both targets might be different also. Although the histologic studies suggest that the difference would be positive, studies comparing the survival of patients treated with and without MRS information included in the treatment plan are required for verification.

Discriminating Progressive Tumor From Radiation Effects Radiation-induced gliosis and necrosis can mimic recurrent tumor on anatomic images by exhibiting features such as contrast-enhancement on T1-weighted MRI and increased volume of hyperintensity on T2-weighted MRI. Proton MRS studies of patients treated with radiotherapy routinely report increased Cho and decreased NAA in recurrent tumor115,120,121 and decreased Cho that persists for several months and is often accompanied by a decrease in tCr and NAA in radiation-induced necrosis.115,120 However, these observations are not always clear-cut due to transient metabolic changes in irradiated normal brain that can occur. Decreased NAA was observed in normal brain regions that were previously irradiated with doses ranging from 20 to 66 Gy.84,85,122 Slight increases in Cho have also been reported as a feature of irradiated normal brain.84,85,122 However, the increased ratio of Cho:NAA in these regions is thought to arise primarily from the decrease in NAA,122 which has been shown to recover within 8 months after irradiation.85 The appearance of Lac and Lip in irradiated tumors is a common occurrence but the reasons for their presence are unclear. Lac has been reported as a feature of spectra from both recurrent tumor120 and radiation necrosis.121 Rutkowski et al noted elevations in Lac in normal-appearing contralateral regions of glioma patients with grades II and III tumors 9 to 12 months after they received radiation therapy.122 Lac peaks were not apparent postsurgery and were therefore thought to be radiation effects. Lac was also observed in the high-dose regions, which corresponds to the most likely lo-

cation of tumor recurrence, even though none of the patients had clinical or radiologic evidence of progression at the time of the study. The authors concluded from these results that Lac could not be used to distinguish recurrent tumor from treatment effect. Recent studies from our group reported an increase in the appearance of Lac in low-grade glioma after surgery.123 Further, Graves et al showed that the serial changes in metabolite levels may be more informative than the static levels at a given time point after therapy.124 Thus, serial studies investigating the changes in the postoperative Lac after radiotherapy that include clinical and radiologic follow-up are needed to determine the best way to use the metabolic information provided by MRS to distinguish recurrent tumor from radiation effect.

Conclusion MRS has proven to be an effective tool for evaluating patients with brain tumors, particularly when the basic principles of the technology and origin of the specific metabolic parameters are well understood. This review has detailed the current state of our understanding of 1H-MRS and its utility for managing patients with brain tumors. It is the author’s hope that this information will help clinicians combine data gleaned from spectroscopic studies with other radiologic and clinical parameters to improve the management of individual patients.

Acknowledgment The author would like to thank Daniel B. Vigneron, PhD, Andrea Pirzkall, MD, and Susan Chang, MD of the Departments of Radiology, Radiation Oncology, and Neurosurgery at UCSF for their support during the construction of this review. I am also very grateful to Dr Franklyn Howe of the UK Biomedical Magnetic Resonance Research Group at St George’s Hospital for contributing several of the figures of single-voxel spectra. Last, I am indebted to Sarah J. Nelson Dr. rer. nat. and her colleagues at the Magnetic Resonance Science Center and Brain Tumor Research Center who have enjoyed a long-standing collaboration for many years that has resulted in several of the studies reviewed in this article.

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