British Journal of Neurosurgery, February 2015; 29(1): 77–81 © 2014 The Neurosurgical Foundation ISSN: 0268-8697 print / ISSN 1360-046X online DOI: 10.3109/02688697.2014.957647
ORIGINAL ARTICLE
Magnetic resonance imaging characteristics of typical and atypical/anaplastic meningiomas – Case series and literature review
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
Lee A. Tan1, Tibor Boco1, Andrew K. Johnson1, Francisco F. Rivas2, Saud Ahmed3, Sharon E. Byrd2 & Richard W. Byrne1 1Departments of Neurosurgery, Rush University Medical Center, Chicago, IL, USA, 2Diagnostic Radiology and Nuclear Medicine,
Rush University Medical Center, Chicago, IL, USA, and 3Rush Medical College, Chicago, IL, USA for symptomatic meningiomas is maximal surgical resection, with or without adjuvant radiation depending on the histologic grading.2–4 About 90% of meningiomas are typical meningiomas (WHO grade I), atypical (WHO grade II, 5–7%) and anaplastic (WHO grade III, 1–2%) meningiomas represent only a small portion of these tumors.5–7 However, the atypical/anaplastic group usually behaves more aggressively and carries a much higher risk for recurrence even after gross total resection. Therefore, adjuvant radiation has been used for anaplastic meningiomas, and more recently for atypical meningiomas, with improved outcomes compared to surgical resection alone.2 Computed tomography (CT) and magnetic resonance imaging (MRI) are widely used imaging modalities for evaluation of intracranial lesions including meningiomas. They can provide important information regarding tumor location, mass effect and the extent of edema. Other more subtle imaging characteristics can also provide clinically important information. For example, calcification on CT and hypointensity8 on T2-weighted MRI usually indicate that the tumor mass is firmer and harder; imaging patterns such as “mushrooming”9 or “lobulation”10,11 have been associated with more aggressively behaving tumors. As medical imaging technology becomes more advanced, other MR sequences including diffusion-weighted (DWI), perfusion (MRP), diffusion-tensor (DTI), and MR spectroscopy (MRS) are being increasingly utilized and they can often provide additional information regarding the tumor preoperatively. DWI and apparent diffusion coefficient (ADC) values can demonstrate areas of restricted diffusion, which can often provide clues to tumor grade and aggressiveness.12–16 MR perfusion (MRP) often reveals increased perfusion within tumors and decreased perfusion of surrounding edematous regions.15,17–19 DTI and fractional anisotropy (FA) values, which measure directional diffusion predominance, are useful in evaluating for tumor infiltration20 in addition to their ability for white matter fiber-tracking.12,16,21–26 MR spectroscopy (MRS) provides the ability to quantify metabolite concentration in specified regions, which is often
Abstract Objective. The histologic grades of meningiomas have a significant impact on the risk of recurrence, prognosis, and the need for adjuvant treatment such as radiation therapy. The purpose of this study is to investigate the magnetic resonance imaging (MRI) characteristics of typical and atypical/anaplastic meningiomas. Methods. The medical records of 32 consecutive patients who underwent meningioma resections between April 2004 and November 2006 were retrospectively reviewed. Preoperative MR studies were reviewed by board-certified neuroradiologists. Both univariate and multivariate analyses were used to analyze the MR characteristics of the typical and atypical/anaplastic meningiomas. A review of pertinent literature was also conducted. Results. Thirty-two patients were identified during the study period. Histopathologic examination of the surgical specimens revealed 27 (84.4% Group I) typical meningiomas and 5 (15.6% - Group 2) atypical/ anaplastic meningiomas. The chi-square test showed that restricted diffusion was much more likely to be present in Group 2 (p ⬍ 0.01), and the choline-to-creatinine (Cho/Cr) ratio was significantly higher in Group 2 (8.8 vs. 5.1, p ⫽ 0.01). The multivariate analysis confirmed that the atypical/anaplastic group is much more likely to have restricted diffusion (p ⫽ 0.02) and higher Cho/Cr ratios (p ⫽ 0.03). Conclusion. Meningiomas with restricted diffusion and higher Cho/Cr ratio on MR spectroscopy are more likely to be atypical/anaplastic types. Preoperative MRI utilizing these sequences can provide important information which can be valuable to counsel patients regarding prognosis, risk of recurrence and the need for adjuvant radiation in addition to surgical resection. Keywords: apparent diffusion coefficient; brain tumor; magnetic resonance; meningioma; restricted diffusion; spectroscopy
Introduction Meningiomas are common brain tumors that account for about 25% of intracranial tumors in adults with a 2:1 female gender predilection.1 The mainstay of treatment
Correspondence: Lee A. Tan, MD, Department of Neurosurgery, Rush University Medical Center, 1725 W. Harrison St. Suite 855, Chicago, IL 60612, USA. Tel: ⫹ 419–236-8831. E-mail: [email protected] Received for publication 1 January 2014; accepted 19 August 2014
77
78
L. A. Tan et al.
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
used for differentiation of tumor recurrence from radiation necrosis. Several studies have demonstrated that unlike neuroglial tumors, meningiomas do not show an N-acetyl aspartate peak.13,19,27–30 Necrotic regions of the tumor often produce lactate peaks,31,32 while areas of increased mitosis show increased choline and increased choline-to-creatinine (Cho/Cr) ratio.33,34 To further assess the capacity of these MR sequences in distinguishing typical and atypical/anaplastic meningiomas, we performed a retrospective study examining MR diffusion, perfusion, and spectroscopy in histologically proven meningiomas with a review of pertinent literature.
Materials and methods Medical records The medical records of 32 consecutive patients who underwent meningioma resections between April 2004 and November 2006 were retrospectively reviewed. All final diagnoses were confirmed by pathology reports. Preoperative MR studies including T1 and T2-weighted imaging (T1WI/ T2WI), DWI, MRP, DTI and MRS were reviewed by two board-certified neuroradiologists. The MR imaging characteristics were recorded and compared between the typical meningioma group and atypical/anaplastic group. The chisquared test and multivariate analysis were used to analyze the MR characteristics of the typical and atypical/anaplastic meningioma groups. All statistical analyses were performed using SPSS, version 19 (IBM Corp. Released 2010. IBM SPSS Statistics for Windows, Version 19.0. Armonk, NY: IBM Corp). The results were considered statistically significant if the p value was less than 0.05. A review of pertinent literature was also conducted by searching keywords including “atypical”, “meningioma”, “MRI” on PubMed. Relevant articles pertaining to MRI and their correlation to the histologic grading of meningiomas were reviewed and discussed.
MR protocol The MR study was performed with a 1.5 T superconducting magnet (Signa, GE Medical Systems, Milwaukee, WI). The MR study was performed with a stereotactic head frame over the patient’s head, with a quadrature head coil. The conventional MRI sequences were performed without intravenous contrast in the axial plane with T1-weighted spin echo (SE) (TR/TE 600/14), T2-weighted fast spin echo (FSE) (TR/TE 5400/99), and T2-weighted gradient echo. The matrix was 256 ⫻ 256, field of view (FOV) 22 or 24 cm, slice thickness 5 mm and interslice gap 1 mm. Following the administration of 0.1 mmol/kg of gadolinium, the MRP pulse sequence was performed, and then T1-weighted SE images were obtained in the axial, coronal and sagittal planes. All MR imaging was evaluated by two experienced, board-certified neuroradiologists. Diffusion-weighted MR imaging was obtained with a single shot, spin echo, echo-planar sequence with b values of 0 and 1,000 s/mm2. Trace images were obtained by simultaneous application of diffusion-sensitive gradients in three different directions (x, y, z gradients). The technical parameters were as follows: TR/TE 10,000/126 ms, NEX 1, matrix
128 ⫻ 256, FOV 24 ⫻ 24 cm, slice thickness 5 mm and interslice gap 1 mm. ADC maps were automatically generated with the FuncTool software program. The neuroradiologists performed these measurements on the solid portion of those meningiomas demonstrating restricted diffusion and on the central portion of meningiomas which did not demonstrate restricted diffusion. Regions of interest (ROI) of 0.25 cm2 were used. The mean ADC values and standard deviations were determined. Student’s t-test deviations were used for statistical analyses. A value of p ⬍ 0.05 was considered statistically significant. DTI was obtained by using single-shot echo-planar imaging with sampling of the entire diffusion tensor. Six high b value images corresponding to diffusion measurements in different gradient directions were acquired, followed by a single low b value image. Three signal intensity averages were obtained to increase the signal-to-noise ratio of the images. The low b value was 0 s/mm2, and the high b value was 1000 s/mm2. Axial images were acquired with the following parameters: TR/TE, 7500/75-100; FOV 22 ⫻ 22 cm, 128 ⫻ 128 pixels; section thickness 6 mm with a 1 mm interslice gap; and 22 axial sections. The averaged DTI data sets were used to generate fractional anisotropy (FA) images. FA images were used to evaluate the degree of diffusion anisotropy. Image analysis of the FA was performed by the neuroradiologists on the solid portion of the meningioma demonstrating the lowest fractional anisotropy or on the central portion of those meningiomas without significant difference in the areas of FA. This was performed at an offsite GE workstation using FuncTool. ROI of 0.25 cm2 were used for determination of the mean FA values. MRP was recorded after the administration of 0.1 mmol/kg of gadolinium intravenously with a power injector (Medrad, Indianola, PA) at a rate of 4 ml/s, followed by a 20 ml saline flush at the same rate. T2-weighted dynamic susceptibility contrast-enhance perfusion MR imaging was performed 5 seconds after the beginning of the injection using a gradient-echo echo-planar sequence with the following parameters: TR/TE 1800/40 ms, NEX 1, flip angle 60 degrees, bandwidth 62, matrix 128 ⫻ 128, number of sections 10, section thickness 8 mm without spacing, slices per acquisition 8–10, FOV 22 cm, and acquisition time 90 seconds. A series of 45 dynamic acquisitions were obtained for each section during the bolus injection. The relative cerebral blood volume (rCBV) analysis was performed by the neuroradiologists using FuncTool software from the automatically generated MR perfusion images. A graph was generated using ROI of 0.25 cm2 from the negative enhancement images of the MRP, and a measurement of the volume of the signal change was used as the rCBV measurement. MRS was performed after the pre and post contrast conventional MR imaging and diffusion-weighted imaging. Proton MRS was performed with the PROBE SV software. The post contrast axial T1-weighted images in the true axial plane were used to locate the voxels for MRS. The aim was to obtain an average spectroscopic representation of the largest part of the tumor while avoiding contamination of the sample by bone, fatty scalp tissue, air or cerebrospinal fluid. The MRS was performed with single voxel short and
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
MRI for meningioma grading
79
long point-resolved spectroscopy (PRESS) (TR: 2000 ms, TE: 30 and 144 ms, 64 and 96 acquisitions, respectively) and multi-voxel chemical shift imaging (CSI) using long PRESS pulse sequence. The raw data of MRS was processed through Fourier transformation automatically. Resonances were as follows: choline (Cho) 3.2 ppm, creatinine (Cr) 3.0 ppm, N-acetyl aspirate (NAA) 2.0 ppm, alanine (Ala) 1.5 ppm, lactate 1.33 ppm with inversion on long PRESS, and lipid 0.5–1.5 ppm without inversion on long PRESS. The ratios of metabolites Cho/Cr were calculated on the long PRESS and reviewed by the neuroradiologists. The post-processing of the multivoxel MRS data was performed with the FuncTool software.
(8.8 vs. 5.1, p ⫽ 0.01). Multivariate analysis confirmed that the atypical/anaplastic group is much more likely to have restricted diffusion (p ⫽ 0.02) and higher Cho/Cr ratios (p ⫽ 0.03). Although there was also a trend for lower ADC values for Group 2 in the multivariate analysis, it did not reach statistical significance (p ⫽ 0.10). None of the other MR characteristics including rCBV from MR perfusion, fractional anisotropy from the DTI sequence, and spectroscopically calculated alanine and lipid levels showed statistically significant correlation with meningioma grades in either the Chi-squared test or multivariate analysis. Summaries of MRI imaging characteristics and a review of literature are shown in Tables I and II, respectively.
Results
Discussion
Thirty-two patients were identified during the study period. There were 27 women and 5 men with an average age of 60 years. Twenty-seven patients (84.4% - Group 1) had typical (WHO grade I) meningiomas; five patients (15.6% - Group 2) had atypical/anaplastic (WHO grade II/III) meningiomas. All diagnoses were confirmed and finalized by the boardcertified senior neuropathologist. Univariate analysis using the Chi-squared test revealed that presence of restricted diffusion was much more likely in Group 2 (p ⬍ 0.01), the apparent diffusion coefficient (ADC) values were significantly lower in Group 2 (0.73 ⫻ 10⫺ 3 vs. 0.96 ⫻ 10⫺ 3 cm2/s, p ⫽ 0.03), and the choline-to-creatinine (Cho/Cr) ratio was significantly higher in Group 2 compared to Group 1
Meningiomas are the most frequent extra-axial intracranial neoplasms. Common indications for surgical removal of meningiomas include the presence of neurological symptoms, seizures, and unremitting headaches. Complete resection of accessible, symptomatic meningiomas is often safe and curative. In asymptomatic lesions or those where surgery is technically challenging or dangerous due to preexisting medical conditions, the decision whether to operate can be more difficult. Although biopsy can provide a histologic sample for tumor grading, it still has the inherent risks associated with any intracranial surgery. The inability to predict the growth rate and malignant potential of these meningiomas preoperatively has limited neurosurgeons’
Table I. Patient data, tumor location, and MRI findings. Patient 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Age
Sex
Histology
Location
# of tumors
T1WI
36 77 47 47 60 48 67 67 54 67 49 89 49 74 63 60 74 41 70 56 82 46 51 68 54 55 68 91 31 77 51 50
F F F M F F F F F F F F F F M F F M F F F F F F F F M M F F F M
A* A A A A T# T T T T T T T T T T T T T T T T T T T T T T T T T T
Left lateral ventricle Left frontal parafalcine Right frontal parafalcine Left occipital parafalcine Right frontal parafalcine Right occipital parafalcine Suprasellar Right frontal convexity Left frontal convexity Midline frontal convexity Rt sphenoid Right frontal parafalcine Right cerebellopontine angle Right frontal parafalcine Left temporal Left frontal parafalcine Right temporal Right frontal convexity Right fronto-parietal parafalcine Right parieto-temporal Left parietal parafalcine Left frontal convexity Left occipital convexity Left frontal convexity Left temporal Right sphenoid Left sphenoid Left frontal convexity Midline frontal convexity Mid frontal falx Right parietal convexity Right frontal parafalcine
1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2
↓↓ ↓↓ ↓↓ ↓ ↓ ↓↓ ↓ ↓ ↓ ↓ ↓ iso ↓↓ ↓↓ ↓↓ ↓↓ iso ↓ iso iso iso ↓↓ ↓↓ ↓↓ ↓↓ ↓↓ ↓↓ iso iso ↓↓ iso iso
*A ⫽ atypical/anaplastic; #T ⫽ typical; homo ⫽ homogenous; hetero ⫽ heterogeneous.
T2WI Edema (mm) Ca2⫹⫹ Enhancement Dural Tail ↑↑ ↑↑ ↑↑ ↑ ↑ ↓↓ ↑↑ ↑↑ ↑ ↑↑ ↑↑ iso ↑↑ ↑↑ ↑↑ ↑↑ ↑ ↑↑ ↑↑ ↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↓↓ ↑↑ ↑↑
0 25 0 48 17 0 0 0 0 mild 0 21 0 15 mild 29 28 22 0 0 0 0 0 24 0 0 0 0 0 20 0 60
– – – – – – – – – – – – – – ↑ – – – – – – – – – – – – – – ↑↑ – –
Homo Hetero Homo Hetero Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Cyst wall Homo Homo Hetro Homo Homo Peripheral Homo Homo
No Yes Yes No Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes ⫹/⫺ Yes Yes Yes Yes Yes Yes Yes Yes No No No Yes Yes No Yes No
80
L. A. Tan et al.
Table II. Summary of existing literature on MRI characteristics correlating with histopathologic grading of meningiomas. Typical Atypical/Anaplastic MR characteristics meningioma meningioma
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
Diffusion weighted imaging Restricted diffusion* ADC** MR perfusion rCBV# Diffusion tensor imaging FA# MR spectroscopy Cho/Cr* Lactate#
Likely to be absent Likely to be present Higher value Lower value Decreased
Increased
Lower value
Higher value
Decreased Increased Likely to be absent Likely to be present
rCBV, relative cerebral blood volume; FA, fractional anisotropy. * ⫽ statistically significant in current study in both univariate and multivariate analyses. ** ⫽ statistically significant in current study only in univariate analysis. # ⫽ no statistical significance in current study.
ability to counsel patients regarding the prognosis, risk of tumor recurrence and the need to adjuvant treatment. A reliable, noninvasive diagnostic tool to predict the pathologic nature of meningiomas preoperatively would be tremendously helpful to the neurosurgeons and the patients. Many researchers have tried to use more advanced MR sequences to further characterize brain tumors. Bulakbasi et al. found that ADC value and MR spectroscopy could be used for tumor grading and risk stratification regardless of tumor type.13 In our cohort, we also observed a trend for lower ADC values in atypical/anaplastic meningiomas, however it was not statistically significant in the multivariate analysis (p ⫽ 0.10). This may have been due to the small number of atypical/anaplastic meningiomas in our cohort. However, two separate studies conducted by Filippi et al.35 and Hakyemez et al.36 both demonstrated statistically significant differences in ADC values between typical and atypical/anaplastic meningiomas. Combining the data from our series and the Hakyemez series, which used a nearly identical protocol, the p value falls to 0.006. The predictive power of the ADC value from the combined data can be determined using the mean and standard values for atypical/ anaplastic and typical meningiomas (0.74 ⫻ 10⫺ 3 ⫾ 0.17 and 1.09 ⫻ 10⫺ 3 ⫾ 0.33, respectively). The pre-imaging probability of an atypical/anaplastic meningioma is about 8% based on epidemiology; that probability jumps to 19% when the ADC value is less than or equal 0.8 ⫻ 10⫺ 3. Conversely, the negative predictive value (NPV) for atypical/anaplastic histology with an ADC value over 1.0 ⫻ 10⫺ 3 is greater than 99%. The Cho/Cr ratio is significantly higher in atypical/ anaplastic meningiomas in our cohort. Shino et al. found similar results and determined that Cho/Cr correlated to mitotic index.34 Demir et al. found a mean Cho/Cr value in four atypical meningiomas of 4.44 ⫾ 0.30 (mean ⫾ SD) and 3.39 ⫾ 0.52 in 12 typical meningiomas on short TE spectra, but seven tumors were omitted due to negligible creatinine peaks.33 Using the values for mean and variance, and a pretest probability of atypical histology of 8%, the calculated NPV for Cho/Cr ⬍ 6.0 is greater than 99%. Bulakbasi et al. found a lactate peak in 5 of 8 atypical and only 2 of 28 typical meningiomas13; however, Demir et al. found lactate peaks in only 1 of 6 atypical and 4 of 17 typical meningiomas.33
In our series, 3 of 5 atypical and 7 of 18 typical meningiomas showed lactate peaks, but the results were not statistically significant. Our MR perfusion results did not reach statistical significance, but did show a trend similar to the results of Zhang et al. (5.89 ⫾ 3.86 for malignant and 7.16 ⫾ 4.08 for benign meningiomas).37 While FA values from the DTI sequence may predict the hardness of meningiomas38 as conventional MR cannot,39 our results do not suggest a trend in predicting the histopathologic grade.
Conclusion Meningiomas with restricted diffusion and higher Cho/ Cr ratio on MR spectroscopy are more likely to be atypical/ anaplastic types. A trend for lower ADC values on DWI exist for more aggressive types, but this does not reach statistical significance. Preoperative MRI utilizing these sequences can provide important information which can be valuable to counsel patients regarding prognosis, risk of recurrence and the need for adjuvant radiation in addition to surgical resection.
Declaration of interest: The authors report no declarations of interest. The authors alone are responsible for the content and writing of the paper.
References 1. Claus EB, Bondy ML, Schildkraut JM, et al. Epidemiology of intracranial meningioma. Neurosurgery 2005;57:1088–95; discussion 1088–95. 2. Park HJ, Kang H-C, Kim IH, et al. The role of adjuvant radiotherapy in atypical meningioma. J Neurooncol 2013;115:241–7. 3. Kleihues P, Burger PC, Scheithauer BW. The new WHO classification of brain tumours. Brain Pathol Zurich Switz 1993;3:255–68. 4. Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumours of the Central Nervous System. Acta Neuropathol (Berl). 2007;114:97–109. 5. Kallio M, Sankila R, Hakulinen T, Jääskeläinen J. Factors affecting operative and excess long-term mortality in 935 patients with intracranial meningioma. Neurosurgery 1992;31:2–12. 6. Mahmood A , Caccamo DV, Tomecek FJ, Malik GM. Atypical and malignant meningiomas: a clinicopathological review. Neurosurgery 1993;33:955–63. 7. Maier H, Ofner D, Hittmair A , Kitz K, Budka H. Classic, atypical, and anaplastic meningioma: three histopathological subtypes of clinical relevance. J Neurosurg 1992;77:616–23. 8. Elster AD, Challa VR, Gilbert TH, Richardson DN, Contento JC. Meningiomas: MR and histopathologic features. Radiology 1989;170:857–62. 9. New PF, Hesselink JR, O’Carroll CP, Kleinman GM. Malignant meningiomas: CT and histologic criteria, including a new CT sign. AJNR Am J Neuroradiol 1982;3:267–76. 10. Nakasu S, Nakajima M, Matsumura K, Nakasu Y, Handa J. Meningioma: proliferating potential and clinicoradiological features. Neurosurgery 1995;37:1049–55. 11. Nakasu S, Nakasu Y, Nakajima M, Matsuda M, Handa J. Preoperative identification of meningiomas that are highly likely to recur. J Neurosurg 1999;90:455–62. 12. Bode MK , Ruohonen J, Nieminen MT, Pyhtinen J. Potential of diffusion imaging in brain tumors: a review. Acta Radiol Stockh Swed 1987;47:585–94. 13. Bulakbasi N, Kocaoglu M, Ors F, Tayfun C, Uçöz T. Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors. AJNR Am J Neuroradiol 2003;24:225–33.
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
MRI for meningioma grading 14. Krabbe K , Gideon P, Wagn P, et al. MR diffusion imaging of human intracranial tumours. Neuroradiology 1997;39:483–9. 15. Provenzale JM, Mukundan S, Barboriak DP. Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response. Radiology 2006;239: 632–49. 16. Provenzale JM, McGraw P, Mhatre P, Guo AC, Delong D. Peritumoral brain regions in gliomas and meningiomas: investigation with isotropic diffusion-weighted MR imaging and diffusion-tensor MR imaging. Radiology 2004;232:451–60. 17. Kremer S, Grand S, Rémy C, et al. Contribution of dynamic contrast MR imaging to the differentiation between dural metastasis and meningioma. Neuroradiology 2004;46:642–8. 18. Uematsu H, Maeda M, Itoh H. Peritumoral brain edema in intracranial meningiomas evaluated by dynamic perfusionweighted MR imaging: a preliminary study. Eur Radiol 2003;13: 758–62. 19. Weber MA , Zoubaa S, Schlieter M, et al. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 2006;66:1899–906. 20. Jolapara M, Kesavadas C, Radhakrishnan VV, et al. Role of diffusion tensor imaging in differentiating subtypes of meningiomas. J Neuroradiol 2010;37:277–83. 21. Cruz Júnior LCH, Sorensen AG. Diffusion tensor magnetic resonance imaging of brain tumors. Neurosurg Clin N Am 2005;16:115–34. 22. Lu S, Ahn D, Johnson G, et al. Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 2004; 232:221–8. 23. Melhem ER, Mori S, Mukundan G, et al. Diffusion tensor MR imaging of the brain and white matter tractography. AJR Am J Roentgenol 2002;178:3–16. 24. Ozsunar Y, Grant PE, Huisman TAGM, et al. Evolution of water diffusion and anisotropy in hyperacute stroke: significant correlation between fractional anisotropy and T2. AJNR Am J Neuroradiol 2004;25:699–705. 25. Sundgren PC, Dong Q, Gómez-Hassan D, et al. Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 2004;46:339–50. 26. Toh C-H, Wong AM-C, Wei K-C, et al. Peritumoral edema of meningiomas and metastatic brain tumors: differences in
27. 28. 29. 30. 31. 32.
33. 34.
35. 36. 37. 38. 39.
81
diffusion characteristics evaluated with diffusion-tensor MR imaging. Neuroradiology 2007;49:489–94. Castillo M, Kwock L. Clinical applications of proton magnetic resonance spectroscopy in the evaluation of common intracranial tumors. Top Magn Reson Imaging TMRI 1999;10:104–13. Gill SS, Thomas DG, Van Bruggen N, et al. Proton MR spectroscopy of intracranial tumours: in vivo and in vitro studies. J Comput Assist Tomogr 1990;14:497–504. Majós C, Alonso J, Aguilera C, et al. Utility of proton MR spectroscopy in the diagnosis of radiologically atypical intracranial meningiomas. Neuroradiology 2003;45:129–36. Sibtain NA , Howe FA , Saunders DE. The clinical value of proton magnetic resonance spectroscopy in adult brain tumours. Clin Radiol 2007;62:109–19. Buhl R, Nabavi A , Wolff S, et al. MR spectroscopy in patients with intracranial meningiomas. Neurol Res 2007;29:43–6. Harting I, Hartmann M, Bonsanto MM, Sommer C, Sartor K . Characterization of necrotic meningioma using diffusion MRI, perfusion MRI, and MR spectroscopy: case report and review of the literature. Neuroradiology 2004;46:189–93. Demir MK, Iplikcioglu AC, Dincer A , Arslan M, Sav A . Single voxel proton MR spectroscopy findings of typical and atypical intracranial meningiomas. Eur J Radiol 2006;60:48–55. Shino A , Nakasu S, Matsuda M, et al. Noninvasive evaluation of the malignant potential of intracranial meningiomas performed using proton magnetic resonance spectroscopy. J Neurosurg 1999;91:928–34. Filippi CG, Edgar MA , Ulug˘ AM, et al. Appearance of meningiomas on diffusion-weighted images: correlating diffusion constants with histopathologic findings. AJNR Am J Neuroradiol 2001;22:65–72. Hakyemez B, Yildirim N, Gokalp G, Erdogan C, Parlak M. The contribution of diffusion-weighted MR imaging to distinguishing typical from atypical meningiomas. Neuroradiology 2006;48:513–20. Zhang H, Rödiger LA , Shen T, Miao J, Oudkerk M. Perfusion MR imaging for differentiation of benign and malignant meningiomas. Neuroradiology 2008;50:525–30. Kashimura H, Inoue T, Ogasawara K, et al. Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging. J Neurosurg 2007;107:784–7. Yamaguchi N, Kawase T, Sagoh M, et al. Prediction of consistency of meningiomas with preoperative magnetic resonance imaging. Surg Neurol 1997;48:579–83.
ORIGINAL ARTICLE
Magnetic resonance imaging characteristics of typical and atypical/anaplastic meningiomas – Case series and literature review
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
Lee A. Tan1, Tibor Boco1, Andrew K. Johnson1, Francisco F. Rivas2, Saud Ahmed3, Sharon E. Byrd2 & Richard W. Byrne1 1Departments of Neurosurgery, Rush University Medical Center, Chicago, IL, USA, 2Diagnostic Radiology and Nuclear Medicine,
Rush University Medical Center, Chicago, IL, USA, and 3Rush Medical College, Chicago, IL, USA for symptomatic meningiomas is maximal surgical resection, with or without adjuvant radiation depending on the histologic grading.2–4 About 90% of meningiomas are typical meningiomas (WHO grade I), atypical (WHO grade II, 5–7%) and anaplastic (WHO grade III, 1–2%) meningiomas represent only a small portion of these tumors.5–7 However, the atypical/anaplastic group usually behaves more aggressively and carries a much higher risk for recurrence even after gross total resection. Therefore, adjuvant radiation has been used for anaplastic meningiomas, and more recently for atypical meningiomas, with improved outcomes compared to surgical resection alone.2 Computed tomography (CT) and magnetic resonance imaging (MRI) are widely used imaging modalities for evaluation of intracranial lesions including meningiomas. They can provide important information regarding tumor location, mass effect and the extent of edema. Other more subtle imaging characteristics can also provide clinically important information. For example, calcification on CT and hypointensity8 on T2-weighted MRI usually indicate that the tumor mass is firmer and harder; imaging patterns such as “mushrooming”9 or “lobulation”10,11 have been associated with more aggressively behaving tumors. As medical imaging technology becomes more advanced, other MR sequences including diffusion-weighted (DWI), perfusion (MRP), diffusion-tensor (DTI), and MR spectroscopy (MRS) are being increasingly utilized and they can often provide additional information regarding the tumor preoperatively. DWI and apparent diffusion coefficient (ADC) values can demonstrate areas of restricted diffusion, which can often provide clues to tumor grade and aggressiveness.12–16 MR perfusion (MRP) often reveals increased perfusion within tumors and decreased perfusion of surrounding edematous regions.15,17–19 DTI and fractional anisotropy (FA) values, which measure directional diffusion predominance, are useful in evaluating for tumor infiltration20 in addition to their ability for white matter fiber-tracking.12,16,21–26 MR spectroscopy (MRS) provides the ability to quantify metabolite concentration in specified regions, which is often
Abstract Objective. The histologic grades of meningiomas have a significant impact on the risk of recurrence, prognosis, and the need for adjuvant treatment such as radiation therapy. The purpose of this study is to investigate the magnetic resonance imaging (MRI) characteristics of typical and atypical/anaplastic meningiomas. Methods. The medical records of 32 consecutive patients who underwent meningioma resections between April 2004 and November 2006 were retrospectively reviewed. Preoperative MR studies were reviewed by board-certified neuroradiologists. Both univariate and multivariate analyses were used to analyze the MR characteristics of the typical and atypical/anaplastic meningiomas. A review of pertinent literature was also conducted. Results. Thirty-two patients were identified during the study period. Histopathologic examination of the surgical specimens revealed 27 (84.4% Group I) typical meningiomas and 5 (15.6% - Group 2) atypical/ anaplastic meningiomas. The chi-square test showed that restricted diffusion was much more likely to be present in Group 2 (p ⬍ 0.01), and the choline-to-creatinine (Cho/Cr) ratio was significantly higher in Group 2 (8.8 vs. 5.1, p ⫽ 0.01). The multivariate analysis confirmed that the atypical/anaplastic group is much more likely to have restricted diffusion (p ⫽ 0.02) and higher Cho/Cr ratios (p ⫽ 0.03). Conclusion. Meningiomas with restricted diffusion and higher Cho/Cr ratio on MR spectroscopy are more likely to be atypical/anaplastic types. Preoperative MRI utilizing these sequences can provide important information which can be valuable to counsel patients regarding prognosis, risk of recurrence and the need for adjuvant radiation in addition to surgical resection. Keywords: apparent diffusion coefficient; brain tumor; magnetic resonance; meningioma; restricted diffusion; spectroscopy
Introduction Meningiomas are common brain tumors that account for about 25% of intracranial tumors in adults with a 2:1 female gender predilection.1 The mainstay of treatment
Correspondence: Lee A. Tan, MD, Department of Neurosurgery, Rush University Medical Center, 1725 W. Harrison St. Suite 855, Chicago, IL 60612, USA. Tel: ⫹ 419–236-8831. E-mail: [email protected] Received for publication 1 January 2014; accepted 19 August 2014
77
78
L. A. Tan et al.
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
used for differentiation of tumor recurrence from radiation necrosis. Several studies have demonstrated that unlike neuroglial tumors, meningiomas do not show an N-acetyl aspartate peak.13,19,27–30 Necrotic regions of the tumor often produce lactate peaks,31,32 while areas of increased mitosis show increased choline and increased choline-to-creatinine (Cho/Cr) ratio.33,34 To further assess the capacity of these MR sequences in distinguishing typical and atypical/anaplastic meningiomas, we performed a retrospective study examining MR diffusion, perfusion, and spectroscopy in histologically proven meningiomas with a review of pertinent literature.
Materials and methods Medical records The medical records of 32 consecutive patients who underwent meningioma resections between April 2004 and November 2006 were retrospectively reviewed. All final diagnoses were confirmed by pathology reports. Preoperative MR studies including T1 and T2-weighted imaging (T1WI/ T2WI), DWI, MRP, DTI and MRS were reviewed by two board-certified neuroradiologists. The MR imaging characteristics were recorded and compared between the typical meningioma group and atypical/anaplastic group. The chisquared test and multivariate analysis were used to analyze the MR characteristics of the typical and atypical/anaplastic meningioma groups. All statistical analyses were performed using SPSS, version 19 (IBM Corp. Released 2010. IBM SPSS Statistics for Windows, Version 19.0. Armonk, NY: IBM Corp). The results were considered statistically significant if the p value was less than 0.05. A review of pertinent literature was also conducted by searching keywords including “atypical”, “meningioma”, “MRI” on PubMed. Relevant articles pertaining to MRI and their correlation to the histologic grading of meningiomas were reviewed and discussed.
MR protocol The MR study was performed with a 1.5 T superconducting magnet (Signa, GE Medical Systems, Milwaukee, WI). The MR study was performed with a stereotactic head frame over the patient’s head, with a quadrature head coil. The conventional MRI sequences were performed without intravenous contrast in the axial plane with T1-weighted spin echo (SE) (TR/TE 600/14), T2-weighted fast spin echo (FSE) (TR/TE 5400/99), and T2-weighted gradient echo. The matrix was 256 ⫻ 256, field of view (FOV) 22 or 24 cm, slice thickness 5 mm and interslice gap 1 mm. Following the administration of 0.1 mmol/kg of gadolinium, the MRP pulse sequence was performed, and then T1-weighted SE images were obtained in the axial, coronal and sagittal planes. All MR imaging was evaluated by two experienced, board-certified neuroradiologists. Diffusion-weighted MR imaging was obtained with a single shot, spin echo, echo-planar sequence with b values of 0 and 1,000 s/mm2. Trace images were obtained by simultaneous application of diffusion-sensitive gradients in three different directions (x, y, z gradients). The technical parameters were as follows: TR/TE 10,000/126 ms, NEX 1, matrix
128 ⫻ 256, FOV 24 ⫻ 24 cm, slice thickness 5 mm and interslice gap 1 mm. ADC maps were automatically generated with the FuncTool software program. The neuroradiologists performed these measurements on the solid portion of those meningiomas demonstrating restricted diffusion and on the central portion of meningiomas which did not demonstrate restricted diffusion. Regions of interest (ROI) of 0.25 cm2 were used. The mean ADC values and standard deviations were determined. Student’s t-test deviations were used for statistical analyses. A value of p ⬍ 0.05 was considered statistically significant. DTI was obtained by using single-shot echo-planar imaging with sampling of the entire diffusion tensor. Six high b value images corresponding to diffusion measurements in different gradient directions were acquired, followed by a single low b value image. Three signal intensity averages were obtained to increase the signal-to-noise ratio of the images. The low b value was 0 s/mm2, and the high b value was 1000 s/mm2. Axial images were acquired with the following parameters: TR/TE, 7500/75-100; FOV 22 ⫻ 22 cm, 128 ⫻ 128 pixels; section thickness 6 mm with a 1 mm interslice gap; and 22 axial sections. The averaged DTI data sets were used to generate fractional anisotropy (FA) images. FA images were used to evaluate the degree of diffusion anisotropy. Image analysis of the FA was performed by the neuroradiologists on the solid portion of the meningioma demonstrating the lowest fractional anisotropy or on the central portion of those meningiomas without significant difference in the areas of FA. This was performed at an offsite GE workstation using FuncTool. ROI of 0.25 cm2 were used for determination of the mean FA values. MRP was recorded after the administration of 0.1 mmol/kg of gadolinium intravenously with a power injector (Medrad, Indianola, PA) at a rate of 4 ml/s, followed by a 20 ml saline flush at the same rate. T2-weighted dynamic susceptibility contrast-enhance perfusion MR imaging was performed 5 seconds after the beginning of the injection using a gradient-echo echo-planar sequence with the following parameters: TR/TE 1800/40 ms, NEX 1, flip angle 60 degrees, bandwidth 62, matrix 128 ⫻ 128, number of sections 10, section thickness 8 mm without spacing, slices per acquisition 8–10, FOV 22 cm, and acquisition time 90 seconds. A series of 45 dynamic acquisitions were obtained for each section during the bolus injection. The relative cerebral blood volume (rCBV) analysis was performed by the neuroradiologists using FuncTool software from the automatically generated MR perfusion images. A graph was generated using ROI of 0.25 cm2 from the negative enhancement images of the MRP, and a measurement of the volume of the signal change was used as the rCBV measurement. MRS was performed after the pre and post contrast conventional MR imaging and diffusion-weighted imaging. Proton MRS was performed with the PROBE SV software. The post contrast axial T1-weighted images in the true axial plane were used to locate the voxels for MRS. The aim was to obtain an average spectroscopic representation of the largest part of the tumor while avoiding contamination of the sample by bone, fatty scalp tissue, air or cerebrospinal fluid. The MRS was performed with single voxel short and
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
MRI for meningioma grading
79
long point-resolved spectroscopy (PRESS) (TR: 2000 ms, TE: 30 and 144 ms, 64 and 96 acquisitions, respectively) and multi-voxel chemical shift imaging (CSI) using long PRESS pulse sequence. The raw data of MRS was processed through Fourier transformation automatically. Resonances were as follows: choline (Cho) 3.2 ppm, creatinine (Cr) 3.0 ppm, N-acetyl aspirate (NAA) 2.0 ppm, alanine (Ala) 1.5 ppm, lactate 1.33 ppm with inversion on long PRESS, and lipid 0.5–1.5 ppm without inversion on long PRESS. The ratios of metabolites Cho/Cr were calculated on the long PRESS and reviewed by the neuroradiologists. The post-processing of the multivoxel MRS data was performed with the FuncTool software.
(8.8 vs. 5.1, p ⫽ 0.01). Multivariate analysis confirmed that the atypical/anaplastic group is much more likely to have restricted diffusion (p ⫽ 0.02) and higher Cho/Cr ratios (p ⫽ 0.03). Although there was also a trend for lower ADC values for Group 2 in the multivariate analysis, it did not reach statistical significance (p ⫽ 0.10). None of the other MR characteristics including rCBV from MR perfusion, fractional anisotropy from the DTI sequence, and spectroscopically calculated alanine and lipid levels showed statistically significant correlation with meningioma grades in either the Chi-squared test or multivariate analysis. Summaries of MRI imaging characteristics and a review of literature are shown in Tables I and II, respectively.
Results
Discussion
Thirty-two patients were identified during the study period. There were 27 women and 5 men with an average age of 60 years. Twenty-seven patients (84.4% - Group 1) had typical (WHO grade I) meningiomas; five patients (15.6% - Group 2) had atypical/anaplastic (WHO grade II/III) meningiomas. All diagnoses were confirmed and finalized by the boardcertified senior neuropathologist. Univariate analysis using the Chi-squared test revealed that presence of restricted diffusion was much more likely in Group 2 (p ⬍ 0.01), the apparent diffusion coefficient (ADC) values were significantly lower in Group 2 (0.73 ⫻ 10⫺ 3 vs. 0.96 ⫻ 10⫺ 3 cm2/s, p ⫽ 0.03), and the choline-to-creatinine (Cho/Cr) ratio was significantly higher in Group 2 compared to Group 1
Meningiomas are the most frequent extra-axial intracranial neoplasms. Common indications for surgical removal of meningiomas include the presence of neurological symptoms, seizures, and unremitting headaches. Complete resection of accessible, symptomatic meningiomas is often safe and curative. In asymptomatic lesions or those where surgery is technically challenging or dangerous due to preexisting medical conditions, the decision whether to operate can be more difficult. Although biopsy can provide a histologic sample for tumor grading, it still has the inherent risks associated with any intracranial surgery. The inability to predict the growth rate and malignant potential of these meningiomas preoperatively has limited neurosurgeons’
Table I. Patient data, tumor location, and MRI findings. Patient 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Age
Sex
Histology
Location
# of tumors
T1WI
36 77 47 47 60 48 67 67 54 67 49 89 49 74 63 60 74 41 70 56 82 46 51 68 54 55 68 91 31 77 51 50
F F F M F F F F F F F F F F M F F M F F F F F F F F M M F F F M
A* A A A A T# T T T T T T T T T T T T T T T T T T T T T T T T T T
Left lateral ventricle Left frontal parafalcine Right frontal parafalcine Left occipital parafalcine Right frontal parafalcine Right occipital parafalcine Suprasellar Right frontal convexity Left frontal convexity Midline frontal convexity Rt sphenoid Right frontal parafalcine Right cerebellopontine angle Right frontal parafalcine Left temporal Left frontal parafalcine Right temporal Right frontal convexity Right fronto-parietal parafalcine Right parieto-temporal Left parietal parafalcine Left frontal convexity Left occipital convexity Left frontal convexity Left temporal Right sphenoid Left sphenoid Left frontal convexity Midline frontal convexity Mid frontal falx Right parietal convexity Right frontal parafalcine
1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2
↓↓ ↓↓ ↓↓ ↓ ↓ ↓↓ ↓ ↓ ↓ ↓ ↓ iso ↓↓ ↓↓ ↓↓ ↓↓ iso ↓ iso iso iso ↓↓ ↓↓ ↓↓ ↓↓ ↓↓ ↓↓ iso iso ↓↓ iso iso
*A ⫽ atypical/anaplastic; #T ⫽ typical; homo ⫽ homogenous; hetero ⫽ heterogeneous.
T2WI Edema (mm) Ca2⫹⫹ Enhancement Dural Tail ↑↑ ↑↑ ↑↑ ↑ ↑ ↓↓ ↑↑ ↑↑ ↑ ↑↑ ↑↑ iso ↑↑ ↑↑ ↑↑ ↑↑ ↑ ↑↑ ↑↑ ↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↓↓ ↑↑ ↑↑
0 25 0 48 17 0 0 0 0 mild 0 21 0 15 mild 29 28 22 0 0 0 0 0 24 0 0 0 0 0 20 0 60
– – – – – – – – – – – – – – ↑ – – – – – – – – – – – – – – ↑↑ – –
Homo Hetero Homo Hetero Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Homo Cyst wall Homo Homo Hetro Homo Homo Peripheral Homo Homo
No Yes Yes No Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes ⫹/⫺ Yes Yes Yes Yes Yes Yes Yes Yes No No No Yes Yes No Yes No
80
L. A. Tan et al.
Table II. Summary of existing literature on MRI characteristics correlating with histopathologic grading of meningiomas. Typical Atypical/Anaplastic MR characteristics meningioma meningioma
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
Diffusion weighted imaging Restricted diffusion* ADC** MR perfusion rCBV# Diffusion tensor imaging FA# MR spectroscopy Cho/Cr* Lactate#
Likely to be absent Likely to be present Higher value Lower value Decreased
Increased
Lower value
Higher value
Decreased Increased Likely to be absent Likely to be present
rCBV, relative cerebral blood volume; FA, fractional anisotropy. * ⫽ statistically significant in current study in both univariate and multivariate analyses. ** ⫽ statistically significant in current study only in univariate analysis. # ⫽ no statistical significance in current study.
ability to counsel patients regarding the prognosis, risk of tumor recurrence and the need to adjuvant treatment. A reliable, noninvasive diagnostic tool to predict the pathologic nature of meningiomas preoperatively would be tremendously helpful to the neurosurgeons and the patients. Many researchers have tried to use more advanced MR sequences to further characterize brain tumors. Bulakbasi et al. found that ADC value and MR spectroscopy could be used for tumor grading and risk stratification regardless of tumor type.13 In our cohort, we also observed a trend for lower ADC values in atypical/anaplastic meningiomas, however it was not statistically significant in the multivariate analysis (p ⫽ 0.10). This may have been due to the small number of atypical/anaplastic meningiomas in our cohort. However, two separate studies conducted by Filippi et al.35 and Hakyemez et al.36 both demonstrated statistically significant differences in ADC values between typical and atypical/anaplastic meningiomas. Combining the data from our series and the Hakyemez series, which used a nearly identical protocol, the p value falls to 0.006. The predictive power of the ADC value from the combined data can be determined using the mean and standard values for atypical/ anaplastic and typical meningiomas (0.74 ⫻ 10⫺ 3 ⫾ 0.17 and 1.09 ⫻ 10⫺ 3 ⫾ 0.33, respectively). The pre-imaging probability of an atypical/anaplastic meningioma is about 8% based on epidemiology; that probability jumps to 19% when the ADC value is less than or equal 0.8 ⫻ 10⫺ 3. Conversely, the negative predictive value (NPV) for atypical/anaplastic histology with an ADC value over 1.0 ⫻ 10⫺ 3 is greater than 99%. The Cho/Cr ratio is significantly higher in atypical/ anaplastic meningiomas in our cohort. Shino et al. found similar results and determined that Cho/Cr correlated to mitotic index.34 Demir et al. found a mean Cho/Cr value in four atypical meningiomas of 4.44 ⫾ 0.30 (mean ⫾ SD) and 3.39 ⫾ 0.52 in 12 typical meningiomas on short TE spectra, but seven tumors were omitted due to negligible creatinine peaks.33 Using the values for mean and variance, and a pretest probability of atypical histology of 8%, the calculated NPV for Cho/Cr ⬍ 6.0 is greater than 99%. Bulakbasi et al. found a lactate peak in 5 of 8 atypical and only 2 of 28 typical meningiomas13; however, Demir et al. found lactate peaks in only 1 of 6 atypical and 4 of 17 typical meningiomas.33
In our series, 3 of 5 atypical and 7 of 18 typical meningiomas showed lactate peaks, but the results were not statistically significant. Our MR perfusion results did not reach statistical significance, but did show a trend similar to the results of Zhang et al. (5.89 ⫾ 3.86 for malignant and 7.16 ⫾ 4.08 for benign meningiomas).37 While FA values from the DTI sequence may predict the hardness of meningiomas38 as conventional MR cannot,39 our results do not suggest a trend in predicting the histopathologic grade.
Conclusion Meningiomas with restricted diffusion and higher Cho/ Cr ratio on MR spectroscopy are more likely to be atypical/ anaplastic types. A trend for lower ADC values on DWI exist for more aggressive types, but this does not reach statistical significance. Preoperative MRI utilizing these sequences can provide important information which can be valuable to counsel patients regarding prognosis, risk of recurrence and the need for adjuvant radiation in addition to surgical resection.
Declaration of interest: The authors report no declarations of interest. The authors alone are responsible for the content and writing of the paper.
References 1. Claus EB, Bondy ML, Schildkraut JM, et al. Epidemiology of intracranial meningioma. Neurosurgery 2005;57:1088–95; discussion 1088–95. 2. Park HJ, Kang H-C, Kim IH, et al. The role of adjuvant radiotherapy in atypical meningioma. J Neurooncol 2013;115:241–7. 3. Kleihues P, Burger PC, Scheithauer BW. The new WHO classification of brain tumours. Brain Pathol Zurich Switz 1993;3:255–68. 4. Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumours of the Central Nervous System. Acta Neuropathol (Berl). 2007;114:97–109. 5. Kallio M, Sankila R, Hakulinen T, Jääskeläinen J. Factors affecting operative and excess long-term mortality in 935 patients with intracranial meningioma. Neurosurgery 1992;31:2–12. 6. Mahmood A , Caccamo DV, Tomecek FJ, Malik GM. Atypical and malignant meningiomas: a clinicopathological review. Neurosurgery 1993;33:955–63. 7. Maier H, Ofner D, Hittmair A , Kitz K, Budka H. Classic, atypical, and anaplastic meningioma: three histopathological subtypes of clinical relevance. J Neurosurg 1992;77:616–23. 8. Elster AD, Challa VR, Gilbert TH, Richardson DN, Contento JC. Meningiomas: MR and histopathologic features. Radiology 1989;170:857–62. 9. New PF, Hesselink JR, O’Carroll CP, Kleinman GM. Malignant meningiomas: CT and histologic criteria, including a new CT sign. AJNR Am J Neuroradiol 1982;3:267–76. 10. Nakasu S, Nakajima M, Matsumura K, Nakasu Y, Handa J. Meningioma: proliferating potential and clinicoradiological features. Neurosurgery 1995;37:1049–55. 11. Nakasu S, Nakasu Y, Nakajima M, Matsuda M, Handa J. Preoperative identification of meningiomas that are highly likely to recur. J Neurosurg 1999;90:455–62. 12. Bode MK , Ruohonen J, Nieminen MT, Pyhtinen J. Potential of diffusion imaging in brain tumors: a review. Acta Radiol Stockh Swed 1987;47:585–94. 13. Bulakbasi N, Kocaoglu M, Ors F, Tayfun C, Uçöz T. Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors. AJNR Am J Neuroradiol 2003;24:225–33.
Br J Neurosurg Downloaded from informahealthcare.com by Biblioteka Uniwersytetu Warszawskiego on 03/23/15 For personal use only.
MRI for meningioma grading 14. Krabbe K , Gideon P, Wagn P, et al. MR diffusion imaging of human intracranial tumours. Neuroradiology 1997;39:483–9. 15. Provenzale JM, Mukundan S, Barboriak DP. Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response. Radiology 2006;239: 632–49. 16. Provenzale JM, McGraw P, Mhatre P, Guo AC, Delong D. Peritumoral brain regions in gliomas and meningiomas: investigation with isotropic diffusion-weighted MR imaging and diffusion-tensor MR imaging. Radiology 2004;232:451–60. 17. Kremer S, Grand S, Rémy C, et al. Contribution of dynamic contrast MR imaging to the differentiation between dural metastasis and meningioma. Neuroradiology 2004;46:642–8. 18. Uematsu H, Maeda M, Itoh H. Peritumoral brain edema in intracranial meningiomas evaluated by dynamic perfusionweighted MR imaging: a preliminary study. Eur Radiol 2003;13: 758–62. 19. Weber MA , Zoubaa S, Schlieter M, et al. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 2006;66:1899–906. 20. Jolapara M, Kesavadas C, Radhakrishnan VV, et al. Role of diffusion tensor imaging in differentiating subtypes of meningiomas. J Neuroradiol 2010;37:277–83. 21. Cruz Júnior LCH, Sorensen AG. Diffusion tensor magnetic resonance imaging of brain tumors. Neurosurg Clin N Am 2005;16:115–34. 22. Lu S, Ahn D, Johnson G, et al. Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 2004; 232:221–8. 23. Melhem ER, Mori S, Mukundan G, et al. Diffusion tensor MR imaging of the brain and white matter tractography. AJR Am J Roentgenol 2002;178:3–16. 24. Ozsunar Y, Grant PE, Huisman TAGM, et al. Evolution of water diffusion and anisotropy in hyperacute stroke: significant correlation between fractional anisotropy and T2. AJNR Am J Neuroradiol 2004;25:699–705. 25. Sundgren PC, Dong Q, Gómez-Hassan D, et al. Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 2004;46:339–50. 26. Toh C-H, Wong AM-C, Wei K-C, et al. Peritumoral edema of meningiomas and metastatic brain tumors: differences in
27. 28. 29. 30. 31. 32.
33. 34.
35. 36. 37. 38. 39.
81
diffusion characteristics evaluated with diffusion-tensor MR imaging. Neuroradiology 2007;49:489–94. Castillo M, Kwock L. Clinical applications of proton magnetic resonance spectroscopy in the evaluation of common intracranial tumors. Top Magn Reson Imaging TMRI 1999;10:104–13. Gill SS, Thomas DG, Van Bruggen N, et al. Proton MR spectroscopy of intracranial tumours: in vivo and in vitro studies. J Comput Assist Tomogr 1990;14:497–504. Majós C, Alonso J, Aguilera C, et al. Utility of proton MR spectroscopy in the diagnosis of radiologically atypical intracranial meningiomas. Neuroradiology 2003;45:129–36. Sibtain NA , Howe FA , Saunders DE. The clinical value of proton magnetic resonance spectroscopy in adult brain tumours. Clin Radiol 2007;62:109–19. Buhl R, Nabavi A , Wolff S, et al. MR spectroscopy in patients with intracranial meningiomas. Neurol Res 2007;29:43–6. Harting I, Hartmann M, Bonsanto MM, Sommer C, Sartor K . Characterization of necrotic meningioma using diffusion MRI, perfusion MRI, and MR spectroscopy: case report and review of the literature. Neuroradiology 2004;46:189–93. Demir MK, Iplikcioglu AC, Dincer A , Arslan M, Sav A . Single voxel proton MR spectroscopy findings of typical and atypical intracranial meningiomas. Eur J Radiol 2006;60:48–55. Shino A , Nakasu S, Matsuda M, et al. Noninvasive evaluation of the malignant potential of intracranial meningiomas performed using proton magnetic resonance spectroscopy. J Neurosurg 1999;91:928–34. Filippi CG, Edgar MA , Ulug˘ AM, et al. Appearance of meningiomas on diffusion-weighted images: correlating diffusion constants with histopathologic findings. AJNR Am J Neuroradiol 2001;22:65–72. Hakyemez B, Yildirim N, Gokalp G, Erdogan C, Parlak M. The contribution of diffusion-weighted MR imaging to distinguishing typical from atypical meningiomas. Neuroradiology 2006;48:513–20. Zhang H, Rödiger LA , Shen T, Miao J, Oudkerk M. Perfusion MR imaging for differentiation of benign and malignant meningiomas. Neuroradiology 2008;50:525–30. Kashimura H, Inoue T, Ogasawara K, et al. Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging. J Neurosurg 2007;107:784–7. Yamaguchi N, Kawase T, Sagoh M, et al. Prediction of consistency of meningiomas with preoperative magnetic resonance imaging. Surg Neurol 1997;48:579–83.
