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Limitations of conventional light microscopy in pathological diagnosis of brain tumors include subjective bias in interpretation and discordance of nomenclature. A study using mid-infrared (IR) spectromicroscopy was undertaken to determine whether meningiomas, a group of brain tumors prone to recurrence, could be identified by the unique spectral 'fingerprints' of their chemical composition. Paired, thin (5-microm) cryosections of snap-frozen human meningioma tumor samples removed at elective surgery were mounted on glass (hematoxylin and eosin-stained tissue section) and infrared (unstained tissue section) reflectance slides, respectively. Concordance of the tumor-bearing areas identified in the stained section by a pathologist with the unstained IR tissue section was ensured using a novel digital grid and tumor-mapping system developed in our laboratory. Compared with the normal control, tumor samples from four meningioma patients revealed a marked decrease in bands associated with unsaturated fatty acids, particularly in the bands at 3010, 2920, 2850, and 1735 cm(-1). Spectral datasets were subjected to hierarchical cluster analyses (HCA) using Ward's algorithm for comparison and grouping of similar data groups, and were converted into color-coded digital maps for matching spectra with their respective clusters. False color images of 5 and 6 clusters obtained by HCA identified dominant clusters corresponding to tumor tissue. Corroboration of these findings in a larger number of meningiomas may allow for more precise identification of these and other types of brain tumors.

Fourier transform infrared spectromicroscopy and hierarchical cluster analysis of human meningiomas