Multimodal multisample spectroscopic imaging analysis of tumor tissues using multivariate curve resolution

Chemical imaging aims to characterize the molecular patterns present in a tissue or surface. High-resolution images with high content of information represent clear advantage many research areas, such as biomedicine. Specific patterns, when related pathological traits, could help understanding events condition studied. composition different regions within may reveal interesting that cannot be detected using conventional staining techniques. In this work, new chemometrics approach is proposed for simultaneous multimodal chemical analysis six slices from two types tumor tissues (EG and 1070) exhibiting sensitivity docetaxel drug. Therefore, deeper study these fingerprints susceptibility response drug treatment. The spectral techniques used were MALDI-TOF mass spectrometry (MSI) FT-IR hyperspectral imaging. addition, RGB color picture hematoxylin/eosin was also included joint image analysis. huge data generated by multiple samples organized combined multiset structures which then analyzed multivariate curve resolution. Using approach, nature constituents their high-resolution spatial distribution detangled showing what main specific areas distinguished tumors. summary, application resolution confirmed powerful flexible tool able extract huge, fused sets obtained type spectroscopic having powers.