Multiscale Topology Characterises Dynamic Tumour Vascular Networks

TL;DR

This paper introduces a multiscale topological data analysis approach to characterize and quantify the complex, dynamic structures of tumour vascular networks, revealing insights into their morphological changes under different treatments.

Contribution

It develops two novel topological lenses for multiscale analysis of vascular networks, surpassing existing single-scale methods and enabling detailed spatio-temporal quantification.

Findings

Quantifies dynamic changes in vessel twists and loops.

Validates known effects of antibodies and radiotherapy on vasculature.

Provides a new framework for analyzing vascular network morphology.

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. Here 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.