SP 4 - Fibromap

Using high throughput imaging and deep learning to develop novel diagnostic and prognostic tools for organ fibrosis

High spatial tissue mapping is now an important part of the validation process and potential applications of multi-dimensional data. Pathophysiological processes, including the development of organ fibrosis, can now be better understood in vivo using complex tissue analysis. In this subproject, we will use state-of-the-art tissue processing, imaging technologies and quantitative tools to validate in vivo multi-omics data generated by the Fibromap consortium. We will analyse tissue in three-dimension with single cell resolution using a combination of multiple optical clearing technologies and advanced light microscopy. Tissue molecular profiling will be performed based on iterative indirect immunofluorescence imaging, a novel technique developed by our team. Finally, high-throughput quantification will be achieved using convolutional neural networks. Therefore, the general aim of this subproject is to develop novel diagnostic and prognostic tools to assess organ fibrosis.

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