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Neuroradiology |
1 From the Departments of Radiology (M.L., S.O., J.S.B., E.W., M.I., E.A.K., G.J.), Pathology (D.Z.), and Neurosurgery (D.Z., E.A.K.), New York University Medical Center, MRI Department, Schwartz Building, Basement HCC, 530 First Ave, New York, NY 10016. Received December 23, 2004; revision requested February 23, 2005; revision received March 30; final version accepted May 2. Supported by grant RO1CA093992 from the National Institutes of Health. Address correspondence to M.L. (e-mail: lawm01{at}med.nyu.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Materials and Methods: Approval for this retrospective HIPAA-compliant study was obtained from the Institutional Board of Research Associates, with waiver of informed consent. Thirty-five patients (23 male and 12 female patients; median age, 39 years; range, 4–80 years) with histologically diagnosed low-grade gliomas (21 low-grade astrocytomas and 14 low-grade oligodendrogliomas and low-grade mixed oligoastrocytomas) were examined with dynamic susceptibility-weighted contrast material–enhanced perfusion magnetic resonance (MR) imaging. Wilcoxon tests were used to compare patients in different response categories (complete response, stable, progressive, death) with respect to baseline relative CBV. Kaplan-Meier survival curves, log-rank tests, and Weibull survival models were used to characterize and evaluate the association of baseline relative CBV with time to progression. Tumor volumes and relative CBV measurements were obtained at initial examination and follow-up.
Results: Lesions with relative CBV less than 1.75 had a median time to progression of 4620 days ± 433 (standard deviation), and lesions with relative CBV more than 1.75 had a median time to progression of 245 days ± 62. Patients who had an adverse event (either death or progression) had significantly higher (P = .003) relative CBV than did patients without adverse events (either complete response or stable disease). Lesions with low baseline relative CBV had stable tumor volumes at follow-up over time, whereas those with high baseline relative CBV (>1.75) had progressively increasing tumor volumes over time.
Conclusion: Dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging can help to identify low-grade gliomas that will progress rapidly and a subset of low-grade gliomas that have a propensity for malignant transformation.
© RSNA, 2006
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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The current reference standard for determining glioma grade is histopathologic assessment. However, the limitations of histopathologic assessment are well known: (a) possible sampling error (since only a few small samples of tissue are assessed, particularly with stereotactic biopsy, the most malignant portion of a tumor may not be sampled); (b) difficulty in obtaining a range of samples if the tumor is inaccessible to the surgeon; (c) the large range of classification and grading systems used at different institutions; (d) interpathologist and intrapathologist variability; and (e) the dynamic nature of central nervous system tumors, with at least 10% dedifferentiating into more malignant grades; some neurosurgeons believe that, given time, all low-grade gliomas will dedifferentiate (2,3). As a result, therapy and clinical outcome based on histopathologic assessment of low-grade gliomas are fraught with potential error.
Dynamic susceptibility-weighted contrast material–enhanced perfusion magnetic resonance (MR) imaging provides images of the entire brain that give physiologic information about neovascularity and angiogenesis (4–10). Since vascular proliferation is an important characteristic of astrocytomas (11), this imaging technique may provide a means of characterizing glioma malignancy that overcomes some of the limitations of histopathologic sampling error. The purpose of this study, therefore, was to determine retrospectively whether relative cerebral blood volume (CBV) measurements can be used to predict clinical response in patients with low-grade gliomas.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Each patient was assigned to one of four clinical response categories on the basis of data obtained at review of the clinical charts and of MR imaging findings performed by two authors (S.O. and E.W., both with 5 years of experience with brain MR imaging). The four categories were complete response, stable disease, progressive disease, and death. These were based in part on the method described by Levin et al (13). A complete response was defined as an MR image with no visible tumor and no new neurologic deficit. Stable disease was defined as no change in the patient's neurologic examination findings or Karnofsky score and a change in tumor size of less than 25% at MR imaging. Progressive disease was defined as a decline in neurologic status or Karnofsky score or an increase in tumor size of more than 25% at MR imaging. Assessment of the patients was performed by the neuro-oncologist at 3-month intervals, when MR imaging also was performed.
Conventional MR Imaging and Tumor Volume Measurements
Imaging was performed with 1.5-T systems (Siemens Vision or Symphony; Siemens, Erlangen, Germany). A localizing sagittal T1-weighted image was obtained, and additional images were obtained with the following sequences: nonenhanced transverse T1-weighted spin echo, with 600/14 (repetition time msec/echo time msec); transverse fluid-attenuated inversion recovery (FLAIR), with 9000/110/2500 (repetition time msec/echo time msec/inversion msec); and T2-weighted (3400/119) MR imaging. Contrast-enhanced transverse T1-weighted MR imaging was performed after acquisition of dynamic susceptibility-weighted perfusion contrast-enhanced MR imaging data. Regions of interest (ROIs) were drawn around the enhancing region of the tumor and around the hyperintense region on T2-weighted or FLAIR images to generate tumor volumes with Medical Image Display and Analysis System (or MIDAS) software (14). ROI analysis was done retrospectively. Each ROI was independently checked for accuracy by the other observer, and any changes were made by joint agreement. The observers were experienced senior board-certified neuroradiologists (E.W. and M.I., both with 5 years of experience in brain MR imaging).
Dynamic Susceptibility-weighted Perfusion Contrast-enhanced MR Imaging
Dynamic susceptibility-weighted perfusion contrast-enhanced MR images were acquired with a gradient-echo echo-planar imaging sequence during the first pass of a standard-dose (0.1 mmol/kg) bolus of gadopentetate dimeglumine (Magnevist; Berlex Laboratories, Wayne, NJ). Seven to 10 sections were positioned to cover the tumor based on T2-weighted and FLAIR images. Imaging parameters were as follows: 1000/54; field of view, 230 x 230 mm; section thickness, 5 mm; matrix, 128 x 128; in-plane voxel size, 1.8 x 1.8 mm; intersection gap, 0%–30%; flip angle, 30°; signal bandwidth, 1470 Hz/pixel. Contrast material was injected at a rate of 5 mL/sec, followed by a 20-mL bolus of saline at a rate of 5 mL/sec. The injection rate was 5 mL/sec in all patients, except for the three patients in the 0–9-year age group, in whom the injection rate was reduced to 3 mL/sec. A total of 60 images were acquired at 1-second intervals, with the injection occurring at the fifth image, so that the bolus would typically arrive at the 15th to 20th image.
Relative CBV Measurements
The procedure used to calculate relative CBV from the dynamic susceptibility-weighted perfusion contrast-enhanced MR imaging data was based on standard algorithms that have been previously described (8,15,16). A summary of the analysis is provided. During the first pass of the bolus of contrast agent, T2* was reduced, and hence, the signal intensity on T2*-weighted images decreased. The change in relaxation rate (
R2*) (ie, the change in the reciprocal of T2*) can be calculated from the signal intensity with the following equation: R2*(t) = {–ln[S(t)/S0]}/TE, where S(t) is the signal intensity at time t, S0 is the unenhanced signal intensity, and TE is the echo time. R2* is proportional to the concentration of contrast agent in the tissue, and CBV is proportional to the area under the curve of R2*(t), provided there is no recirculation or leakage of contrast agent. In general, these assumptions are violated, but the effects can be reduced by fitting a gamma-variate function to the measured R2* curve. This function approximates the curve that would have been obtained without recirculation or leakage. CBV can then be estimated from the area under the fitted curve rather than from the original data.
The analysis outlined here does not give an absolute measurement of CBV but rather provides a ratio and, hence, does not have any units. It is therefore usual to calculate relative CBV, which is the ratio of the CBV of an area relative to that measured in some standard tissue, typically normal white matter. ROIs were placed in the region of maximal relative CBV and referenced to the mirror-image ROI placed in the contralateral white matter for a lesion in the white matter and the contralateral normal gray matter for a lesion in the gray matter.
Data processing was performed with a workstation (Unix; The Open Group, San Francisco, Calif) and programs developed in house with C and Interactive Data Language programming languages. Color overlay maps of relative CBV were calculated. To improve the signal-to-noise ratio, however, the relative CBV measurements used in this study were calculated from ROIs placed in regions of highest perfusion seen on the relative CBV color overlay maps. Four separate ROI measurements were made, and the maximum value was recorded. It has been demonstrated that this method for the measurement of maximal abnormality provides the highest intra- and interobserver reproducibility in relative CBV measurements (17). To minimize confounding factors in relative CBV analysis, the size of the ROIs was kept constant (radius = 3.6 mm). The relative CBV measurements were obtained by a board-certified neuroradiologist (M.L.) with 6 years of experience in perfusion data acquisition at our institution.
Statistical Analysis
Means, standard deviations, and medians of relative CBV measurements were obtained for patients in each clinical response category (complete response, stable, progressive, death). Wilcoxon tests were used to compare patients in different clinical response categories with respect to baseline relative CBV. Weibull survival models were used to evaluate the association between relative CBV and survival and time to progression. Time to progression is defined as the time from the initial surgical diagnosis to the time of decline in neurologic status or Karnofsky score or increase in tumor size by more than 25% at MR imaging.
Patients were classified into two groups, those with low relative CBV and those with high relative CBV, with a threshold value of 1.75. This threshold value previously had been found to give the optimal sensitivity and specificity for differentiating low-grade gliomas from high-grade gliomas in a logistic regression analysis of 120 high-grade gliomas and 40 low-grade gliomas (6). Kaplan-Meier survival curves and the log-rank test were used to characterize and compare the group with high relative CBV and the group with low relative CBV in terms of overall survival and time to progression. All statistical computations were performed with software (SAS System for Windows, version 9.0, 2002; SAS Institute, Cary, NC), and results were declared statistically significant at the two-sided 5% comparisonwise significance level (ie, P < .05). Data for those patients with complete response and stable disease at the time of most recent follow-up were appropriately censored. Binary logistic regression analysis was used to determine whether age, sex, resection versus biopsy, presence or absence of enhancement, tumor volume, and CBV were significant predictors of an adverse event (progression or death).
Least-squares regression analysis was conducted to examine the association between relative CBV and changes in T1 and T2 volumes after adjustment for the potential confounding effects of age and sex. For the regression analyses, the change in T1 or T2 volume was used as the dependent variable, and baseline relative CBV and the change in relative CBV were considered as linear numeric predictors in separate analyses. In each case, the model included age and sex as fixed classification factors. The analyses were conducted both with and without inclusion of terms that represented the interaction of relative CBV with age and sex, as well as with and without deletion of the data from those of the subjects with an inordinately high increase in both T1 and T2 volumes.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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With Weibull survival models, neither age (P = .339) nor sex (P = .90) was associated with overall survival, whereas relative CBV exhibited a significant negative association with survival (P = .001), such that low relative CBV values were associated with longer survival times. The same basic conclusion held for time to progression: Neither age (P = .312) nor sex (P = .285) was associated with time to progression, whereas relative CBV exhibited a significant negative association with disease-free survival (P = .001) such that low relative CBV values were associated with longer times to progression.
The nonparametric plot for disease-free survival created by using the Kaplan-Meier method (Fig 1) demonstrates that lesions with relative CBVs less than 1.75 (n = 16) had a median time to progression of 4620 days ± 433 (standard deviation), whereas lesions with relative CBVs that were more than 1.75 (n = 19) had a median time to progression of 245 days ± 62 (P < .005). Binary logistic regression indicated that neither patient age (P = .141) nor sex (P = .267) were significant predictors of an adverse event (progression or death), whereas relative CBV was a significant predictor of adverse outcomes both with and without adjustment for age and sex (P = .027 and .012, respectively).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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In this study, we demonstrated that relative CBV measurements may be used to predict tumor progression and clinical response. This method may be comparable to, if not better than, the current reference standard. Problems with the current standard may be caused by histologic sampling error or inter- and intrapathologist variability in interpretation. It is also possible that relative CBV measurements indicate changes in blood volume that precede malignant transformation. In a review of patient outcome with low-grade glioma (grade II) by the Cairncross group, the median survival (n = 167; mean age, 40.6 years) was 10.5 years (18). The diagnoses included pathologically confirmed supratentorial low-grade fibrillary astrocytoma, oligodendroglioma, and mixed oligoastrocytoma. Given these data, even though we are comparing median time to progression with median survival, all of the patients with lesions in our study should have had a median survival of beyond 10 years. However, it is clear from the results that low-grade gliomas with relative CBVs of more than 1.75 were demonstrating much more rapid time to progression (245 days or 8 months), which is more in line with the median survival for glioblastoma multiforme (grade IV) (19).
The most common cause of death in patients with a low-grade glioma is dedifferentiation into a high-grade glioma. Aronen et al (20) found that glial tumors with a relative CBV greater than 1.5 were more likely to develop into high-grade gliomas at some point during follow-up. It is unclear, however, whether some of these lesions already had high-grade components or whether an elevated relative CBV indicates early vascular proliferation in a lesion that is undergoing malignant transformation. Recently, Tzika et al (21) demonstrated that blood volume measurements could be used to distinguish between progressive and stable tumors (P = .03) in pediatric patients. Similarly, Lev et al (5) showed that relative CBV elevation was a stronger predictor of both tumor grade and survival than was the degree of enhancement. The correlation for survival was also stronger with relative CBV than with contrast enhancement. That study showed a mean survival of 91 months ± 14 for relative CBVs of less than 1.5 versus 24 months ± 27 for relative CBVs of more than 1.5. This finding is comparable to our results, which indicated a median time to progression of 154 months ± 14 for relative CBVs less than 1.75 and 8 months ± 2 for relative CBVs more than 1.75.
It is clear from both studies that lesions with higher relative CBVs are more likely to behave in the manner of a high-grade glioma, such as glioblastoma multiforme, whereas those with lower relative CBVs are more likely to have an outcome more in keeping with a true low-grade glioma, despite their initial histopathologic diagnosis. It is important to note that the relative CBV value of 1.75 is dependent on the imaging parameters and protocols used clinically at our institution, and, hence, caution must be exercised in applying the specific numeric values of this study to another clinical practice. In a study of 73 patients with glioma, Schmainda et al (22) were able to classify correctly 96% of high-grade gliomas but only 69% of low-grade gliomas by means of dynamic contrast-enhanced MR imaging. Similarly, Law et al (6) found a sensitivity of 95.0% but a specificity of only 57.5% for the prediction of high-grade glioma with dynamic susceptibility-weighted perfusion contrast-enhanced MR imaging in 160 patients. In view of the findings of this study, it seems highly likely that if a clinical end point, rather than histologic diagnosis, were considered as the reference standard for tumor grading, these studies would have demonstrated much greater specificity. That is, tumors that were classified as low-grade glioma at histologic analysis but high-grade glioma at dynamic susceptibility-weighted perfusion contrast-enhanced MR imaging were either high grade at the time of the study or underwent malignant transformation after the histologic assessment was made.
It is clear from the literature that conventional imaging findings, such as the absence of contrast enhancement, are independent prognostic factors for either survival or progression-free survival (5,23–28). In this study, 46% of the lesions did not show enhancement after contrast material administration. There was also no association between the presence or absence of contrast enhancement and the time to progression. Despite this lack of association, most institutional algorithms for the treatment of low-grade gliomas are based on imaging findings such as lesion size, the presence or degree of contrast enhancement, and mass effect (28). As a result, the triaging of patients who have a lesion with an imaging diagnosis of low-grade glioma is controversial and highly variable from one center to another (28). By the same token, there are limited data in regard to outcomes such as time to progression, malignant transformation, mortality, and morbidity in patients withlow-grade gliomas (29). This compounds the difficulty, evident from the literature, in the determination of optimal treatment strategies for low-grade gliomas. Advanced MR imaging techniques, such as dynamic susceptibility-weighted perfusion contrast-enhanced MR imaging, may provide such an objective measure of disease malignancy and activity.
One potential limitation of our study was the effect of surgical resection versus biopsy on time to progression. It is important to note from our data that the time to progression in patients whose diagnosis was determined at stereotactic biopsy alone (2063 days; n = 14) was very similar to that in patients whose diagnosis was determined at stereotactic resection (2366 days; n = 21). Researchers in a recent review of the literature, in which the outcome was analyzed by means of multivariate methods, found no clear consensus that, in patients who underwent either biopsy or limited or gross total resection, the time to progression or survival in patients with low-grade gliomas was affected (28). It must be noted that, in this study, although there was no difference between patients who underwent biopsy and patients who underwent resection in regard to time to progression, the extent of tumor resection may have had an effect on patient outcome. The majority of patients (10 of 13) with no adverse event (and relative CBV < 1.75) underwent resection, whereas more than half (seven of 13) of those with an adverse event (and relative CBV > 1.75) underwent biopsy only.
A second limitation of our study was the potential effect of different treatment protocols on the time to progression. The initial treatment protocol for low-grade gliomas at our institution included either stereotactic resection or biopsy, with or without radiation therapy. Of patients with low-grade gliomas and low relative CBV (n = 16), five did not receive adjuvant radiation therapy after surgery, and three received radiation therapy to the surgical bed. Of the patients who received radiation treatment, the average dose of conformal fractionated external–photon beam radiation was 58.3 Gy (range, 54.0–63.0 Gy). The remaining eight only received a combination of radiation therapy and chemotherapy, which consisted of temozolomide (Temodar; Schering, Kenilworth, NJ), carboplatin (Paraplatin; Bristol-Myers Squibb, New York, NY), and/or a combination of procarbazine, lomustine (chloroethyl-cyclohexyl-nitrosourea), and vincristine (Mutulane; Sigma-Tau Pharmaceuticals, Gaithersburg, Md), only after the tumor was shown to be progressive but not at the initial diagnosis. Of patients with low-grade gliomas with high relative CBV (n = 19), seven did not receive adjuvant radiation therapy after surgery, one received radiation therapy to the surgical bed, two received chemotherapy only (either temozolomide or a combination of procarbazine, lomustine, and vincristine), and nine received a combination of radiation therapy and chemotherapy (temozolomide; a combination of procarbazine, lomustine, and vincristine; or a combination of temozolomide and high-dose carboplatin), only after the tumor was shown to be progressive. Therefore, chemotherapeutic agents were not routinely administered at the time of surgery, and diagnosis and should not be a confounding factor.
Furthermore, in both groups the majority of patients either received no adjuvant therapy or they underwent both surgery and radiation therapy in approximately the same proportions, since the histopathologic grades were the same, so it is unlikely that the treatment protocol had a major effect on our overall results. There are also no clear data demonstrating that any particular treatment regimen produces radically better outcomes than are produced by the others, so that differences in the treatment protocol should not substantially affect patient outcome for low-grade gliomas. It is well known that some lesions respond to some therapies, while others respond to different therapies, and still others respond to no therapy at all, even though they are classified as the same grade of tumor (22).
For the neurosurgeon and neuro-oncologist, any and all preoperative information on the aggressiveness of a glioma affects decision making before, during, and after surgery. This is especially true, given the noted discordance between histopathologic grade and contrast enhancement. This information may alter the neurosurgeon's risk-versus-benefit equation. Knowing preoperatively that a lesion has a high relative CBV can affect the decision to resect close to eloquent regions of the brain. The vascularity of a glioma may influence the planned size, shape, and extent of craniotomy or help a neurosurgeon choose between biopsy and resection. After surgery, the vascularity of a lesion may help determine whether aggressive adjuvant therapy should be used or may affect the choice of adjuvant therapies, especially the use of antiangiogenesis treatments. It may also influence the clinician's decision as to follow-up intervals.
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FOOTNOTES |
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Abbreviations: CBV = cerebral blood volume • FLAIR = fluid-attenuated inversion recovery • ROI = region of interest • WHO = World Health Organization
Authors stated no financial relationship to disclose.
Author contributions: Guarantor of integrity of entire study, M.L.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; literature research, M.L., S.O., E.W., M.I., D.Z., E.A.K., G.J.; clinical studies, all authors; statistical analysis, M.L., S.O., J.S.B., M.I.; and manuscript editing, all authors
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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