Multimodal Imaging to Delineate Tumor Heterogeneity in Cerebral Gliomas
Astrid Ellen Grams, Jens Gempt, Florian Ringel, Eric Soehngen, Sabrina Astner, Jürgen Schlegel, Bernhard Meyer, Claus Zimmer, Annette Förschler
Department of Neuropathology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany;Department of Neuropathology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
Department of Neuroradiology, Medical University Innsbruck, Innsbruck, Austria.
Department of Neurosurgery, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
Department of Radiation Oncology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
DOI: 10.4236/ojrad.2014.42024   PDF    HTML     5,962 Downloads   7,356 Views   Citations


Purpose: Magnetic resonance imaging (MRI) is the gold standard in visualizing brain tumors and their effects on adjacent structures. However, no reliable information concerning different tumor components and borders between perifocal edema and infiltration areas can be received. The aim of the study was to establish and evaluate a multimodal imaging concept, in order to differentiate different biological tumor components and to determine tumor borders. Materials and Methods: 12 patients with cerebral gliomas (four low and eight high grade) received a “morphological” MRI, a 3D MR spectroscopy and a T2* MR perfusion examination prior to surgery. Data was evaluated by defining different tumor components, which were entitled based upon their multimodal characteristics and histological data. Results: In high grade gliomas different components can be differentiated, which were described as: “true edema”, “cellular proliferation”, “vascular proliferation”, “cellular infiltration”, “tumor” and “necrosis”. In low grade gliomas, four different tumor components were found: “true edema”, “cellular infiltration”, “cellular proliferation” and “tumor”. Conclusion: With the applied multimodal imaging and a novel evaluation concept, it was possible to detect different tumor components, which could be helpful in detecting the optimal sites for tumor biopsy. Especially in morphological “edema appearing” sites, this knowledge could be important for the adaption of tumor resection borders and the planning of radiation therapy. Further studies with more patients and histological correlation are needed.

Share and Cite:

Grams, A. , Gempt, J. , Ringel, F. , Soehngen, E. , Astner, S. , Schlegel, J. , Meyer, B. , Zimmer, C. and Förschler, A. (2014) Multimodal Imaging to Delineate Tumor Heterogeneity in Cerebral Gliomas. Open Journal of Radiology, 4, 182-189. doi: 10.4236/ojrad.2014.42024.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] De Angelis, L.M. (2001) Brain Tumors. The New England Journal of Medicine, 344, 114-123.
[2] Stupp, R., Mason, W.P., van den Bent, M.J., et al. (2005) Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. The New England Journal of Medicine, 352, 987-996.
[3] Pouratian, N. and Schiff, D. (2010) Management of Low-Grade Glioma. Current Neurology and Neuroscience Reports, 10, 224-231.
[4] Sartor, K. (1999) MR Imaging of the Brain: Tumors. European Radiology, 9, 1047-1054.
[5] Watanabe, M., Tanaka, R. and Takeda, N. (1992) Magnetic Resonance Imaging and Histopathology of Cerebral Gliomas. Neuroradiology, 34, 463-469.
[6] Simmons, M.L., Frondoza, C.G. and Coyle, J.T. (1991) Immunocytochemical Localization of N-Acetyl-Aspartate with Monoclonal Antibodies. Neuroscience, 45, 37-45.
[7] Michaelis, T., Merboldt, K.D., Bruhn, H., et al. (1993) Absolute Concentrations of Metabolites in the Adult Human Brain in Vivo: Quantification of Localized Proton MR Spectra. Radiology, 187, 219-227.
[8] Herminghaus, S., Pilatus, U., Moller-Hartmann, W., et al. (2002) Increased Choline Levels Coincide with Enhanced Proliferative Activity of Human Neuroepithelial Brain Tumors. NMR in Biomedicine, 15, 385-392.
[9] Soares, D.P. and Law, M. (2009) Magnetic Resonance Spectroscopy of the Brain: Review of Metabolites and Clinical Applications. Clinical Radiology, 64, 12-21.
[10] Di Costanzo, A., Scarabino, T., Trojsi, F., et al. (2008) Proton MR Spectroscopy of Cerebral Gliomas at 3 T: Spatial Heterogeneity, and Tumour Grade and Extent. European Radiology, 18, 1727-1735.
[11] Di Costanzo, A., Scarabino, T., Trojsi, F., et al. (2006) Multiparametric 3T MR Approach to the Assessment of Cerebral Gliomas: Tumor Extent and Malignancy. Neuroradiology, 48, 622-631.
[12] Cha, S., Knopp, E.A., Johnson, G., et al. (2002) Intracranial Mass Lesions: Dynamic Contrast-Enhanced Susceptibility-Weighted Echo-Planar Perfusion MR Imaging. Radiology, 223, 11-29.
[13] Hakyemez, B., Erdogan, C., Bolca, N., et al. (2006) Evaluation of Different Cerebral Mass Lesions by Perfusion-Weighted MR Imaging. Journal of Magnetic Resonance Imaging, 24, 817-824.
[14] Arvinda, H.R., Kesavadas, C., Sarma, P.S., et al. (2009) Glioma Grading: Sensitivity, Specificity, Positive and Negative Predictive Values of Diffusion and Perfusion Imaging. Journal of Neuro-Oncology, 94, 87-96.
[15] Arnold, D.L., Shoubridge, E.A., Villemure, J.G., et al. (1990) Proton and Phosphorus Magnetic Resonance Spectroscopy of Human Astrocytomas in Vivo. Preliminary Observations on Tumor Grading. NMR in Biomedicine, 3, 184-189.
[16] Ott, D., Hennig, J. and Ernst, T. (1993) Human Brain Tumors: Assessment with in Vivo Proton MR Spectroscopy. Radiology, 186, 745-752.
[17] Yamasaki, F., Takaba, J., Ohtaki, M., Abe, N., Kajiwara, Y., Saito, T., Yoshioka, H., Hama, S., Akimitsu, T., Sugiyama, K., Arita, K. and Kurisu, K. (2005) Detection and Differentiation of Lactate and Lipids by Single-Voxel Proton MR Spectroscopy. Neurosurgical Review, 28, 267-277.
[18] Felber, S.R. (1993) 1H Magnetic Resonance Spectroscopy in Intracranial Tumors and Cerebral Ischemia. Der Radiologe, 33, 626-632.
[19] De Stefano, N., Caramanos, Z., Preul, M.C., Francis, G., Antel, J.P. and Arnold, D.L. (1998) In Vivo Differentiation of Astrocytic Brain Tumors and Isolated Demyelinating Lesions of the Type Seen in Multiple Sclerosis Using 1H Magnetic Resonance Spectroscopic Imaging. Annals of Neurology, 44, 273-278.
[20] Dowling, C., Bollen, A.W., Noworolski, S.M., McDermott, M.W., Barbaro, N.M., Day, M.R., Henry, R.G., Chang, S.M., Dillon, W.P., Nelson, S.J. and Vigneron, D.B. (2001) Preoperative Proton MR Spectroscopic Imaging of Brain tumors: Correlation with Histopathologic Analysis of Resection Specimens. AJNR. American Journal of Neuroradiology, 22, 604-612.
[21] Ishimaru, H., Morikawa, M., Iwanaga, S., Kaminogo, M., Ochi, M. and Hayashi, K. (2001) Differentiation between High-Grade Glioma and Metastatic Brain Tumor Using Single-Voxel Proton MR Spectroscopy. European Radiology, 11, 1784-1791.
[22] Chen, J., Huang, S.L., Li, T. and Chen, X.L. (2006) In Vivo Research in Astrocytoma Cell Proliferation with 1H-Magnetic Resonance Spectroscopy: Correlation with Histopathology and Immunohistochemistry. Neuroradiology, 48, 312318.
[23] Shimizu, H., Kumabe, T., Tominaga, T., Kayama, T., Hara, K., Ono, Y., Sato, K., Arai, N., Fujiwara, S. and Yoshimoto, T. (1996) Noninvasive Evaluation of Malignancy of Brain Tumors with Proton MR Spectroscopy. AJNR. American Journal of Neuroradiology, 17, 737-747.
[24] Laprie, A., Catalaa, I., Cassol, E., et al. (2008) Proton Magnetic Resonance Spectroscopic Imaging in Newly Diagnosed Glioblastoma: Predictive Value for the Site of Postradiotherapy Relapse in a Prospective Longitudinal Study. International Journal of Radiation Oncology * Biology * Physics, 70, 773-781.
[25] McKnight, T.R., Lamborn, K.R., Love, T.D., Berger, M.S., Chang, S., Dillon, W.P., Bollen, A. and Nelson, S.J. (2007) Correlation of Magnetic Resonance Spectroscopic and Growth Characteristics within Grades II and III Gliomas. Journal of Neurosurgery, 106, 660-666.
[26] Spampinato, M.V., Smith, J.K., Kwock, L., Ewend, M., Grimme, J.D., Camacho, D.L.A. and Castillo, M. (2007) Cerebral Blood Volume Measurements and Proton MR Spectroscopy in Grading of Oligodendroglial Tumors. AJR. American Journal of Roentgenology, 188, 204-212.
[27] Hakyemez, B., Erdogan, C., Ercan, I., Ergin, N., Uysal, S. and Atahan, S. (2005) High-Grade and Low-Grade Gliomas: Differentiation by Using Perfusion MR Imaging. Clinical Radiology, 60, 493-502.
[28] Aronen, H.J. and Perkio, J. (2002) Dynamic Susceptibility Contrast MRI of Gliomas. Neuroimaging Clinics of North America, 12, 501-523.
[29] Ludemann, L., Grieger, W., Wurm, R., Budzisch, M., Hamm, B. and Zimmer, C. (2001) Comparison of Dynamic Contrast-Enhanced MRI with WHO Tumor Grading for Gliomas. European Radiology, 11, 1231-1241.
[30] Ludemann, L., Hamm, B. and Zimmer, C. (2000) Pharmacokinetic Analysis of Glioma Compartments with Dynamic Gd-DTPA-Enhanced Magnetic Resonance Imaging. Magnetic Resonance Imaging, 18, 1201-1214.
[31] Ludemann, L., Grieger, W., Wurm, R., et al. (2005) Quantitative Measurement of Leakage Volume and Permeability in Gliomas, Meningiomas and Brain Metastases with Dynamic Contrast-Enhanced MRI. Magnetic Resonance Imaging, 23, 833-841.
[32] Sugahara, T., Korogi, Y., Tomiguchi, S., Shigematsu, Y., Ikushima, I., Kira, T., Liang, L., Ushio, Y. and Takahashi, M. (2000) Posttherapeutic Intraaxial Brain Tumor: The Value of Perfusion-Sensitive Contrast-Enhanced MR Imaging for Differentiating Tumor Recurrence from Nonneoplastic Contrast-Enhancing Tissue. AJNR. American Journal of Neuroradiology, 21, 901-909.
[33] Wagner, M., Nafe, R., Jurcoane, A., Pilatus, U., Franz, K., Rieger, J., Steinbach, J.P. and Hattingen, E. (2011) Heterogeneity in Malignant Gliomas: A Magnetic Resonance Analysis of spatial Distribution of Metabolite Changes and Regional Blood Volume. Journal of Neuro-Oncology, 103, 663-672.
[34] Hlaihel, C., Guilloton, L., Guyotat, J., Streichenberger, N., Honnorat, J. and Cotton, F. (2010) Predictive Value of Multimodality MRI Using Conventional, Perfusion, and Spectroscopy MR in Anaplastic Transformation of Low-Grade Oligodendrogliomas. Journal of Neuro-Oncology, 97, 73-80.
[35] Chawalparit, O., Sangruchi, T., Witthiwej, T., Sathornsumetee, S., Tritrakarn, S., Piyapittayanan, S., Chaicharoen, P., Direksunthorn, T. and Charnchaowanish, P. (2013) Diagnostic Performance of Advanced MRI in Differentiating HighGrade from Low-Grade Gliomas in a Setting of Routine Service. Journal of the Medical Association of Thailand = Chotmaihet Thangphaet, 96, 1365-1373.
[36] Yang, I. and Aghi, M.K. (2009) New Advances that Enable Identification of Glioblastoma Recurrence. Nature Reviews Clinical Oncology, 6, 648-657.
[37] Candiota, A.P., Majos, C., Julia-Sape, M., Cabanas, M., Acebes, J.J., Moreno-Torres, A., Griffiths, J.R. and Arús, C. (2011) Non-Invasive Grading of Astrocytic Tumours from the Relative Contents of Myo-Inositol and Glycine Measured by in Vivo MRS. JBR-BTR, 94, 319-329.
[38] Kim, H., Catana, C., Ratai, E.M., Andronesi, O.C., Jennings, D.L., Batchelor, T.T., Jain, R.K. and Sorensen, A.G. (2011) Serial Magnetic Resonance Spectroscopy Reveals a Direct Metabolic Effect of Cediranib in Glioblastoma. Cancer Research, 71, 3745-3752.
[39] Guillevin, R., Menuel, C., Taillibert, S., Capelle, L., Costalat, R., Abud, L., Habas, C., De Marco, G., Hoang-Xuan, K., Chiras, J. and Vallée, J.N. (2011) Predicting the Outcome of Grade II Glioma Treated with Temozolomide Using Proton Magnetic Resonance Spectroscopy. British Journal of Cancer, 104, 1854-1861.
[40] Murphy, P.S., Viviers, L., Abson, C., Rowland, I.J., Brada, M., Leach, M.O. and Dzik-Jurasz, A.S.K. (2004) Monitoring Temozolomide Treatment of Low-Grade Glioma with Proton Magnetic Resonance Spectroscopy. British Journal of Cancer, 90, 781-786.
[41] Zou, Q.G., Xu, H.B., Liu, F., Guo, W., Kong, X.C. and Wu, Y. (2011) In the Assessment of Supratentorial Glioma Grade: The Combined Role of Multivoxel Proton MR Spectroscopy and Diffusion Tensor Imaging. Clinical Radiology, 66, 953-960.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.