The virtual tumour - in silico modelling of tumour vasculature, oxygenation and treatment outcome

by Filippo Schiavo (Stockholm University)

Thursday 19 Dec 2024, 09:00 → 12:00 Europe/Stockholm

(CCK) lecture hall, Visionsgatan 56, Karolinska Hospital (Cancer Centrum Karolinska)

Abstract
Poor tumour oxygenation, namely hypoxia, is one of the major challenges that has been recognised in radiotherapy,
yet it is not being accounted for in standard treatments. Hypoxia, resulting from a heterogeneous distribution of vessels
(chronic hypoxia) or a loss in vascular perfusion (acute hypoxia), affects all kinds of solid tumours to different extents.
Although over-sustained angiogenesis with vascular remodelling is one of the key hallmarks of cancer, the resulting tumour
vasculature is often frail and lacking an organised structure, hence incapable of maintaining the same nutrients and oxygen
supply standards of healthy vascular networks.
Tumour hypoxia correlates with worse disease prognoses when compared to normoxic tumours. Indeed, hypoxic cells
require an up to three times higher radiation dose than normoxic tissues to achieve the same biological effect. However,
many of its biological aspects remain only partially understood.
From this perspective, in silico modelling of the tumour key radiobiological features could instead represent a new
frontier, as unprecedented computational power and numerical optimisation routines permit to expand virtually the set of
possible microenvironmental situations, with simulations of real treatments and concurrent intercomparison of hypothetical
scenarios. The fact that the real vascular anatomy of a deep-seated tumour is not fully accessible – and hence not precisely
modellable – could be compensated by a large record of heterogeneous oxygenation patterns provided by the model, with
inherent best- and worst- case studies. At the same time, in silico modelling would not replace in vivo functional imaging, but
would rather act in synergy with that as an additional layer of study: based on the macroscopic information that for instance
positron emission tomography or magnetic resonance imaging could offer, the underlying microscopic radiobiological
nature of the tumour could be simulated.
This thesis consists of four published papers and an introductory overview of the topics, which provide the background
needed for their basic understanding. Beginning with an account of tumour hypoxia and its radiobiological causes
and implications for the outcome of radiotherapeutic treatments, the computational modelling aspects of hypoxia are
also examined. As the core of a comprehensive project developed during the PhD work, a novel three-dimensional
radiobiological model of the vasculature and oxygenation is presented, including its application to treatment scenarios.
Since one of the main aims of this model is its implementation into a treatment planning system, a proof-of-concept
of such integration will be presented, having in sight more clinically oriented studies of the efficacy of various treatment
scenarios in terms of underlying tumour oxygenation and treatment choices regarding beam quality, fractionation, and total
dose. Examples of these studies were performed in silico, with the support of High Performance Computing centres that
could allow, among other things, the increase in size of the modelled tumours, and the development of a concept emerging
nowadays, that of (in silico) virtual clinical trials, potentially enhancing considerably the current status of clinical trials.
Possible applications of the tumour model extended to other medical fields are also envisioned in this thesis. Finally, an
outlook on the stages reached so far is given, with the aim of showing and with the hope that good ground has been paved
for the goal of a better accounting of tumour hypoxia in the future.