The role of surgery in the management of brain tumors is a delicate balancing act in which the surgeon's goal is to maximize tumor resection while minimizing postoperative neurological deficits. Surgery for gliomas is challenging because of the infiltrative nature of these lesions. Delineation of surgical margins is especially difficult, as the periphery of the tumor becomes indistinguishable from the surrounding normal brain. Neurosurgeons utilize a variety of tools in order to address this problem such as intraoperative MRI, fluorescence labeling, and intraoperative histopathological analysis.1-3 At present, histopathological examination with immunohistochemistry labeling, genetic and proteonomic analysis are collectively considered the gold standards for diagnosis and classification of tumors. However, the lengthy processing time required for these results makes them impractical tools to help guide intraoperative decision making in order to achieve maximal tumor resection.
Recent research published in Proceedings of the National Academy of Science from Purdue University and Brigham and Women's Hospital, demonstrates a novel method to provide accurate intraoperative tumor diagnosis as well as sample composition in near-real time using desorption electrospray ionization mass spectrometry (DESI-MS).4 The technique is performed by direct lipid analysis from tumor samples and takes less than a second to provide the result. The group's initial experiments demonstrated that the DESI-MS technique could distinguish between the lipid profiles of gliomas vs meningiomas. Using 21 banked glioma samples and 11 banked meningioma samples, the group was able to train a computerized classification model to detect the unique lipid profiles of these two tumor types.5 The accuracy of this prediction model was subsequently validated on a second set of 15 gliomas and 8 meningiomas with a 100% agreement between the lipid profile analysis and the histological diagnosis.6
The researchers then applied the DESI-MS technique to tissue samples from 5 stereotactic surgical cases. Tissue samples were registered from MRI images used for image guidance and analyzed ex situ using DESI-MS. The results of the DESI-MS analysis were then correlated to the histopathological analysis. In one of the representative surgical cases (Case 2) seven surgical samples were obtained and analyzed (S7, S8, S10-S13, and S15) by DESI-MS. DESI mass spectra revealed lipid profiles that were characteristic of a low-grade glioma. Changes in the relative abundances of ions due to certain lipid species are observed as a function of grade for oligodendrogliomas. For example, the ratio between specific mass spectra peaks increases as the grade of the oligodendroglioma increases.
When tested for glioma subtype, grade, and tumor cell concentration, agreement was achieved for all samples within all classes when compared to the histological analysis (Table 1). Some anticipated disparity in the DESI-MS and histological analysis was seen mostly in distinguishing between tumor grades II & III. The group justifies these differences based on the inherent heterogeneity of tumor cells especially seen at the margins of the tumor, where neoplastic cells are admixed with normal surrounding brain tissue. Additional testing was performed on 4 other surgical specimens with similar results in which the DESI-MS analysis correlated to histological observations with high fidelity.
In conclusion, DESI-MS is a near-real time intraoperative tumor-analyzing tool that permits rapid, reliable, and reproducible results with regard to tumor type, subtype, grade and concentration. Such information may prove to be invaluable in guiding the neurosurgeon to achieve maximal tumor resection while minimizing the extent of collateral damage to the surrounding normal brain tissue. Although currently at its infancy, the implications of this novel technique are far reaching and hold promise in helping surgeon and patient alike in the treatment of these challenging tumors.
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2. Stummer W, Stocker S, Wagner S, et al.. Intraoperative detection of malignant gliomas by 5-aminolevulinic acid-induced porphyrin fluorescence. Neurosurgery. 1998;42(3):518–525.
3. Liang D, Schulder M. The role of intraoperative magnetic resonance imaging in glioma surgery. Surg Neurol Int. 2012;3(suppl 4):S320–S327.
4. Eberlin LS, Norton I, Orringer D, et al.. Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors. Proc Natl Acad Sci U S A. 2013;110(5):1611–1616.
5. Seeley EH, Schwamborn K, Caprioli RM. Imaging of intact tissue sections: moving beyond the microscope. J Biol Chem. 2011;286(29):25459–25466.
6. Dill AL, Eberlin LS, Ifa DR, Cooks RG. Perspectives in imaging using mass spectrometry. Chem Commun (Camb). 2011;47(10):2741–2746.