Malignant gliomas are very aggressive tumors, highly angiogenic and invading heterogeneously the surrounding brain parenchyma, making their resection very difficult. To overcome the limits of current diagnostic imaging techniques used for gliomas, we proposed using FTIR imaging, with a spatial resolution from 6 to 10 μm, to provide molecular information for their histological examination, based on discrimination between normal and tumor vasculature. Differentiation between normal and tumor blood vessel spectra by hierarchical cluster analysis was performed on tissue sections obtained from xenografted brain tumors of Rag-gamma mice 28 days after intracranial implantation of glioma cells, as well as for human brain tumors obtained in clinics. Classical pathological examination and immunohistochemistry were performed in parallel to the FTIR spectral imaging of brain tissues. First on the animal model, classification of FTIR spectra of blood vessels could be performed using spectral intervals based on fatty acyl (3050-2800 cm(-1)) and carbohydrate (1180-950 cm(-1)) absorptions, with the formation of two clusters corresponding to healthy and tumor parts of the tissue sections. Further data treatments on these two spectral intervals provided interpretable information about the molecular contents involved in the differentiation between normal and tumor blood vessels, the latter presenting a higher level of fatty acyl chain unsaturation and an unexpected loss of absorption from osidic residues. This classification method was further successfully tested on human glioma tissue sections. These findings demonstrate that FTIR imaging could highlight discriminant molecular markers to distinguish between normal and tumor vasculature, and help to delimitate areas of corresponding tissue.