“…Recent work using HRMAS for brain tumors showed that it is possible to classify spectroscopy samples according to tumor histological type [8, 12, 16, 18, 20, 22, 27, 44, 46] and grade [10, 12, 14, 16, 27, 46, 47] using multivariate methods such as linear discriminant analysis [14, 16], support vector machines [12, 14, 16], logistic regression [10, 47], partial least squares discriminant analysis [8], and multi-layer perceptrons [12]. Moreover, HRMAS multivariate studies successfully revealed the status of tumor microheterogeneity [9, 13, 15, 17] and detected alterations in tumor metabolism before changes in morphology occurred [12]. These studies combined dimensionality reduction methods such as principal component analysis [14, 20, 22] and metabolite quantification [10, 14–17, 22, 30, 47] with the robust classification methods listed above.…”