Models of multiscale fluid transport for characterising treatment response in tumours

Lead Research Organisation: University of Leeds
Department Name: Sch of Computing

Abstract

Human tumours show a heterogeneity of response to treatments like chemotherapy. Treatments that don't produce a good response often cause unnecessary side effects and delay the start of effective treatment. Current clinical and imaging approaches to monitoring are insensitive to early changes in tumours that might indicate a favourable response. Tumour blood supply and interstitial flow play an essential role in tumour growth, invasion, and treatment response. Correspondingly, we seek to augment imaging measurements with knowledge of the physics and physiology of the tumour and tissue microenvironment to create fundamentally new ways of discovering early predictors of response.
This project is aimed at formulating models of fluid transport and microstructural change at different spatial scales using multiple-network poroelastic theory (MPET). MPET has recently been used by the main supervisor to create models of multiscale flow within the brain for exploring mechanisms of dementia progression; its application to tumour modelling, and expansion to encompass remodelling phenomena is entirely new.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022732/1 01/10/2019 31/03/2028
2438496 Studentship EP/S022732/1 01/10/2020 30/09/2024 Rose Mathilde Collet