To grow and treat in vitro tumour spheroids (mouse brain and lung) in a nutrient medium as well as the surrounding normal tissue (epidermis)
Rapid versus medium or slow proliferation (CCT adjustment 10 to 30 hours), 120 hour dead cell clearance, LQ radiosensitivity with separate hypoxic and hypoxic terms, 30% repair probability of sublethal damage, 10% G0 phase recruitment, individual cell cycle phase times
Six RT schedules simulated and compared in terms of cell kill to assess TCP and likelihood of epidermal side effects, 3 no./day produced high toxicity and a reduction from 60 to 50 Gy total doses is suggested
Brain tumour growth and RT in a regular 3D lattice
Cell cycle times of 2 or 5 days, regular capillary placement in the lattice, 100 m oxygen diffusion limit to define hypoxia and 140 m to define necrosis, constant OER value of 3.0, 5 day dead cell clearance
Three RT schedules simulated, with accelerated RT more effective on fast growing tumours
Equation-based modelling of hypoxic tumour LQ cell kill for tumours with a 2-compartment oxygen level make-up versus intermediate (0.5 to 20 mm Hg) oxygen values
Radial distance of a cell from the tumour boundary to determine oxygenation (2-component model or complete range of pO2 values considered)
Small impact of full reoxygenation between fractions: hypoxia plays a significant role in determining outcome, 10% hypoxia and Gy radiotherapy equates to 104 times less cell kill using a full pO2 range compared to the 2-component oxygenation model
Simulating lung and brain tumour growth in a 3D lattice to determine optimal individualised RT schedules
Gaussian probability cell cycle times, G0 phase on 25 hours, reoxygenation during shrinkage, S phase versus non-S phase LQ radiosensitivity values, cellular hypoxia if more than three cells from nutrient source, OER ranging from 1.0 to 3.0 with separation into and
values of 3.0 to 3.5 provide cell kill in agreement with cell culture survival curves, accelerated schedules are beneficial, wild type tumours (higher /) respond well compared to mutated tumours
Simulating realistic oxygenation gradients and cell densities to explore their impact on radiosensitivity at both the microscopic and macroscopic scale
Oxygenation, vessel geometry parameters (density, radius, heterogeneity), oxygen consumption rate, distance from a vessel
Vascular heterogeneity impacts significantly on the hypoxic fraction, local and global dose responses are predicted from LQ theory using the initial clonogenic cell number and the effective radiation distance
Mathematical (stochastic components), Popple et al., 2002 [19]
Predicting tumour control probability after selective boosting hypoxic subvolumes within a tumour mass
Reoxygenation between doses, OER of 2.0 for hypoxic cells, boost and nonboost spatial cell compartments.
A 20% to 50% boost in dose to a subpopulation of hypoxic cells increased tumour control probability equal to that of an oxic tumour, a boost dose to regions of transient hypoxia has little effect
Simulating hypoxic tumour growth and RT considering hypoxia and angiogenesis
OER = 2.5 and 3.0 (continuous cell oxygenation range in later work), vessels modelled in a regular lattice, angiogenetic factors to induce vessel growth and hence pO2 delivery to cells, distance of a cell from a vessel.
An increase in capillary cell cycle time affects tumour doubling time as does the intercapillary distance, doses of 86 Gy versus 78 Gy are required to control the simulated tumours for conventional and accelerated schedules, respectively
Mathematical (stochastic components), Daşu et al., 1999–2009 [23–26]
Simulating 2D cell distributions to investigate the effects of cell heterogeneity, hypoxia (acute and chronic) on RT outcome
2-compartment oxygenation (2.5 mm Hg hypoxic threshold) versus full oxygenation range, cell heterogeneity
Temporal oxygenation changes between treatment fractions are less important than the presence of chronic hypoxia, and a small degree of hypoxia during every treatment fraction has an effect on tumour response regardless of the changes in spatial hypoxia, a 2-component hypoxia model is not sufficient in describing tumour oxygenation
Mathematical (stochastic components), Søvik et al., 2007 [27]
Optimising tumour control through redistribution of the delivered dose, “dose painting”
pO2 histograms (0 to 102.5 mm Hg), hypoxia defined by 5.0 mm Hg threshold, reoxygenation modelled, heterogeneous cell density, dose delivery based on four pO2 thresholds: 2.5, 5.0, 20.0, 102.5 mm Hg, and of 2.5 and 3.0, OER equation maximum of 3.28
Prescribing varying doses to different parts of the tumour can significantly increase TCP although the rate of reoxygenation is crucial. Tumours with no reoxygenation have the most benefit of dose redistribution. Chronic hypoxia influences outcome more than acute hypoxia
Simulating cell line specific parameters and functional pre-treatment 3D PET/CT data to investigate the effects of oxygenation on RT outcome
5-day cell dead clearance, 36-hour average cell cycle time, OER with K value of 3.0, full pO2 range, 1 mm Hg necrotic threshold, individual phase radiosensitivities
Tissue growth curves and reoxygenation data follow in vitro and human clinical data, with an accurate time delay of tumour shrinkage predicted
Stochastic, “HYP-RT,” Harriss-Phillips et al., and Tuckwell et al., 2008–2011 [29, 30]
Simulating hypoxic tumour growth and reoxygenation during RT of HNSCC
LQ-based cell kill with OER consideration, full cellular pO2 distribution (1 to 100 mm Hg), OER curve changing with dose per fraction, reoxygenation as well as accelerated repopulation between dose fractions
Hyperfractionation using Gy per day is optimal for HNSCC, hypoxic tumours require 16 Gy extra dose during conventional radiotherapy compared to oxic tumours, and the maximum value and shape of the oxygen enhancement ratio curve that may be dependent on dose per fraction are crucial for prediction of TCP
