Mass Spectrometry Imaging (MSI) is the novel imaging technology for the visualisation and detection of chemical composition in tissue samples. Given the molecular weights of drugs (chemical compounds), biomarkers and metabolites, MSI technology is able to detect and show them simultaneously in the form of a stack of (thousands) images. This certainly created tremendous interests and opportunities in the medical field, to name a few, the investigation of drugs’ efficacy and safety, the correlations MSI signature and biomarkers, as well as the interrogation of complex relationships among drugs, metabolites and biomarkers.
MSI can also be incorporated for cross-modality data interrogation with the widely used tissue imaging technology including Haematoxylin & Eosin (H&E), Immunohistochemistry (IHC) and fluorescent multiplexing. H&E is the principle staining in tissue pathology and the gold standard in diagnosis and investigation of tissue morphology. IHC is widely used labelling method in molecular biology for showing protein biomarkers in tissue, which could be related to a specific biological and cellular phenomenon such as cell division and cell death. Fluorescent multiplexing, on the other hand, is able to show multiple cellular and sub-cellular signalling at exact single cell level, which includes protein and DNA biomarkers.
This project is to investigate and address some of the key challenges faced by using MSI and the combined use of above multiple image modalities, which is the processing multi-modality and multi-dimensional image data. MSI images are intrinsically three dimensional. In the context of drug discovery and disease research, it is often required to test different doses of a same drug, and to observe the efficacy and toxicity of a given drug at different time points. Therefore, this is truly a five dimensional (3D + dynamics + kinetics) data processing and mining question. The multi-modality of images brings other challenges, such as the cross-modality image registration, data visualisation and the investigation of a systematic method of utilising available/relevant data.
This project is in collaboration with AstraZeneca based in Cambridge. AstraZeneca will provide all relevant tissue samples, MSI and other modals of image data. The exact tissue and disease types are to be decided.