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Multiscale Topology Characterises Dynamic Tumour Vascular Networks


ABSTRACT: Advances in imaging techniques enable high resolution 3D visualisation of vascular networks over time and reveal abnormal structural features such as twists and loops, and their quantification is an active area of research. In this study we showcase how topological data analysis (TDA), the mathematical field that studies `shape' of data, can characterise the geometric, spatial and temporal organisation of vascular networks. We propose two topological lenses to study vasculature, which capture inherent multi-scale features and vessel connectivity, and surpass the single scale analysis of existing methods. We analyse images collected using intravital and ultramicroscopy modalities and quantify spatio-temporal variation of twists, loops, and avascular regions (voids) in 3D vascular networks. This topological approach validates and quantifies known qualitative trends such as dynamic changes in tortuosity and loops in response to antibodies that modulate vessel sprouting; furthermore, it quantifies the effect of radiotherapy on vessel architecture. Here, we provide sample images, code for our TDA pipeline, and the barcode outputs that we analysed in our study.

ORGANISM(S): Mus musculus (mouse)

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PROVIDER: S-BSST808 | bioimages |

REPOSITORIES: bioimages

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