Wendy M. Harriss-Phillips

Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer

OBJECTIVE A temporal Monte Carlo tumour growth and radiotherapy effect model (HYP-RT) simulating hypoxia in head and neck cancer has been developed and used to analyse parameters influencing cell kill during conventionally fractionated radiotherapy. The model was designed to simulate individual cell division up to 10(8) cells, while incorporating radiobiological effects, including accelerated repopulation and reoxygenation during treatment. METHOD Reoxygenation of hypoxic tumours has been modelled using randomised increments of oxygen to tumour cells after each treatment fraction. The process of accelerated repopulation has been modelled by increasing the symmetrical stem cell division probability. Both phenomena were onset immediately or after a number of weeks of simulated treatment. RESULTS The extra dose required to control (total cell kill) hypoxic vs oxic tumours was 15-25% (8-20 Gy for 5 × 2 Gy per week) depending on the timing of accelerated repopulation onset. Reoxygenation of hypoxic tumours resulted in resensitisation and reduction in total dose required by approximately 10%, depending on the time of onset. When modelled simultaneously, accelerated repopulation and reoxygenation affected cell kill in hypoxic tumours in a similar manner to when the phenomena were modelled individually; however, the degree was altered, with non-additive results. Simulation results were in good agreement with standard linear quadratic theory; however, differed for more complex comparisons where hypoxia, reoxygenation as well as accelerated repopulation effects were considered. CONCLUSION Simulations have quantitatively confirmed the need for patient individualisation in radiotherapy for hypoxic head and neck tumours, and have shown the benefits of modelling complex and dynamic processes using Monte Carlo methods.

A review of the development of tumor vasculature and its effects on the tumor microenvironment

Background The imbalance of angiogenic regulators in tumors drives tumor angiogenesis and causes the vasculature to develop much differently in tumors than in normal tissue. There are several cancer therapy techniques currently being used and developed that target the tumor vasculature for the treatment of solid tumors. This article reviews the aspects of the tumor vasculature that are relevant to most cancer therapies but particularly to vascular targeting techniques. Materials and methods We conducted a review of identified experiments in which tumors were transplanted into animals to study the development of the tumor vasculature with tumor growth. Quantitative vasculature morphology data for spontaneous human head and neck cancers are reviewed. Parameters assessed include the highest microvascular density (h-MVD) and the relative vascular volume (RVV). The effects of the vasculature on the tumor microenvironment are discussed, including the distributions of hypoxia and proliferation. Results Data for the h-MVD and RVV in head and neck cancers are highly varied, partly due to methodological differences. However, it is clear that the cancers are typically more vascularized than the corresponding normal tissue. The commonly observed chronic hypoxia and acute hypoxia in these tumors are due to high intratumor heterogeneity in MVD and lower than normal blood oxygenation levels through the abnormally developed tumor vasculature. Hypoxic regions are associated with decreased cell proliferation. Conclusion The morphology of the vasculature strongly influences the tumor microenvironment, with important implications for tumor response to medical intervention such as radiotherapy. Quantitative vasculature morphology data herein may be used to inform computational models that simulate the spatial tumor vasculature. Such models may play an important role in exploring and optimizing vascular targeting cancer therapies.

In Silico Modelling of Treatment-Induced Tumour Cell Kill: Developments and Advances

Mathematical and stochastic computer (in silico) models of tumour growth and treatment response of the past and current eras are presented, outlining the aims of the models, model methodology, the key parameters used to describe the tumour system, and treatment modality applied, as well as reported outcomes from simulations. Fractionated radiotherapy, chemotherapy, and combined therapies are reviewed, providing a comprehensive overview of the modelling literature for current modellers and radiobiologists to ignite the interest of other computational scientists and health professionals of the ever evolving and clinically relevant field of tumour modelling.

The HYP-RT Hypoxic Tumour Radiotherapy Algorithm and Accelerated Repopulation Dose per Fraction Study

The HYP-RT model simulates hypoxic tumour growth for head and neck cancer as well as radiotherapy and the effects of accelerated repopulation and reoxygenation. This report outlines algorithm design, parameterisation and the impact of accelerated repopulation on the increase in dose/fraction needed to control the extra cell propagation during accelerated repopulation. Cell kill probabilities are based on Linear Quadratic theory, with oxygenation levels and proliferative capacity influencing cell death. Hypoxia is modelled through oxygen level allocation based on pO2 histograms. Accelerated repopulation is modelled by increasing the stem cell symmetrical division probability, while the process of reoxygenation utilises randomised pO2 increments to the cell population after each treatment fraction. Propagation of 108 tumour cells requires 5–30 minutes. Controlling the extra cell growth induced by accelerated repopulation requires a dose/fraction increase of 0.5–1.0 Gy, in agreement with published reports. The average reoxygenation pO2 increment of 3 mmHg per fraction results in full tumour reoxygenation after shrinkage to approximately 1 mm. HYP-RT is a computationally efficient model simulating tumour growth and radiotherapy, incorporating accelerated repopulation and reoxygenation. It may be used to explore cell kill outcomes during radiotherapy while varying key radiobiological and tumour specific parameters, such as the degree of hypoxia.

Monte-Carlo model development for evaluation of current clinical target volume definition for heterogeneous and hypoxic glioblastoma

Clinical target volume (CTV) determination may be complex and subjective. In this work a microscopic-scale tumour model was developed to evaluate current CTV practices in glioblastoma multiforme (GBM) external radiotherapy. Previously, a Geant4 cell-based dosimetry model was developed to calculate the dose deposited in individual GBM cells. Microscopic extension probability (MEP) models were then developed using Matlab-2012a. The results of the cell-based dosimetry model and MEP models were combined to calculate survival fractions (SF) for CTV margins of 2.0 and 2.5 cm. In the current work, oxygenation and heterogeneous radiosensitivity profiles were incorporated into the GBM model. The genetic heterogeneity was modelled using a range of α/β values (linear-quadratic model parameters) associated with different GBM cell lines. These values were distributed among the cells randomly, taken from a Gaussian-weighted sample of α/β values. Cellular oxygen pressure was distributed randomly taken from a sample weighted to profiles obtained from literature. Three types of GBM models were analysed: homogeneous-normoxic, heterogeneous-normoxic, and heterogeneous-hypoxic. The SF in different regions of the tumour model and the effect of the CTV margin extension from 2.0-2.5 cm on SFs were investigated for three MEP models. The SF within the beam was increased by up to three and two orders of magnitude following incorporation of heterogeneous radiosensitivities and hypoxia, respectively, in the GBM model. However, the total SF was shown to be overdominated by the presence of tumour cells in the penumbra region and to a lesser extent by genetic heterogeneity and hypoxia. CTV extension by 0.5 cm reduced the SF by a maximum of 78.6  ±  3.3%, 78.5  ±  3.3%, and 77.7  ±  3.1% for homogeneous and heterogeneous-normoxic, and heterogeneous hypoxic GBMs, respectively. Monte-Carlo model was developed to quantitatively evaluate SF for genetically heterogeneous and hypoxic GBM with two CTV margins and three MEP distributions. The results suggest that photon therapy may not provide cure for hypoxic and genetically heterogeneous GBM. However, the extension of the CTV margin by 0.5 cm could be beneficial to delay the recurrence time for this tumour type due to significant increase in tumour cell irradiation.

Hypoxia in head and neck cancer in theory and practice: a PET-based imaging approach.

Hypoxia plays an important role in tumour recurrence among head and neck cancer patients. The identification and quantification of hypoxic regions are therefore an essential aspect of disease management. Several predictive assays for tumour oxygenation status have been developed in the past with varying degrees of success. To date, functional imaging techniques employing positron emission tomography (PET) have been shown to be an important tool for both pretreatment assessment and tumour response evaluation during therapy. Hypoxia-specific PET markers have been implemented in several clinics to quantify hypoxic tumour subvolumes for dose painting and personalized treatment planning and delivery. Several new radiotracers are under investigation. PET-derived functional parameters and tracer pharmacokinetics serve as valuable input data for computational models aiming at simulating or interpreting PET acquired data, for the purposes of input into treatment planning or radio/chemotherapy response prediction programs. The present paper aims to cover the current status of hypoxia imaging in head and neck cancer together with the justification for the need and the role of computer models based on PET parameters in understanding patient-specific tumour behaviour.

Evaluation of current clinical target volume definitions for glioblastoma using cell-based dosimetry stochastic methods

OBJECTIVE Determination of an optimal clinical target volume (CTV) is complex and remains uncertain. The aim of this study was to develop a glioblastoma multiforme (GBM) model to be used for evaluation of current CTV practices for external radiotherapy. METHODS The GBM model was structured as follows: (1) a Geant4 cellular model was developed to calculate the absorbed dose in individual cells represented by cubic voxels of 20 μm sides. The system was irradiated with opposing 6 MV X-ray beams. The beams encompassed planning target volumes corresponding to 2.0- and 2.5-cm CTV margins; (2) microscopic extension probability (MEP) models were developed using MATLAB(®) 2012a (MathWorks(®), Natick, MA), based on clinical studies reporting on GBM clonogenic spread; (3) the cellular dose distribution was convolved with the MEP models to evaluate cellular survival fractions (SFs) for both CTV margins. RESULTS A CTV margin of 2.5 cm, compared to a 2.0-cm CTV margin, resulted in a reduced total SF from 12.9% ± 0.9% to 3.6% ± 0.2%, 5.5% ± 0.4% to 1.2% ± 0.1% and 11.1% ± 0.7% to 3.0% ± 0.2% for circular, elliptical and irregular MEP distributions, respectively. CONCLUSION A Monte Carlo model was developed to quantitatively evaluate the impact of GBM CTV margins on total and penumbral SF. The results suggest that the reduction in total SF ranges from 3.5 to 5, when the CTV is extended by 0.5 cm. ADVANCES IN KNOWLEDGE The model provides a quantitative tool for evaluation of different CTV margins in terms of cell kill efficacy. Cellular platform of the tool allows future incorporation of cellular properties of GBM.

Altered fractionation outcomes for hypoxic head and neck cancer using the HYP-RT Monte Carlo model

OBJECTIVE Altered fractionation radiotherapy is simulated on a set of virtual tumours to assess the total doses required for tumour control compared with clinical head and neck data and the doses required to control hypoxic vs well-oxygenated tumours with different radiobiological properties. METHODS The HYP-RT model is utilised to explore the impact of tumour oxygenation and the onset times of accelerated repopulation (AR) and reoxygenation (ROx) during radiotherapy. A biological effective dose analysis is used to rank the schedules based on their relative normal tissue toxicities. RESULTS Altering the onset times of AR and ROx has a large impact on the doses required to achieve tumour control. Immediate onset of ROx and 2-week onset time of AR produce results closely predicting average human outcomes in terms of the total prescription doses in clinical trials. Modifying oxygen enhancement ratio curves based on dose/fraction significantly reduces the dose (5-10 Gy) required for tumour control for hyperfractionated schedules. HYP-RT predicts 10×1.1 Gy per week to be most beneficial, whereas the conventional schedule is predicted as beneficial for early toxicity but has average-poor late toxicity. CONCLUSION HYP-RT predicts that altered radiotherapy schedules increase the therapeutic ratio and may be used to make predictions about the prescription doses required to achieve tumour control for tumours with different oxygenation levels and treatment responses. ADVANCES IN KNOWLEDGE Oxic and hypoxic tumours have large differences in total radiation dose requirements, affected by AR and ROx onset times by up to 15-25 Gy for the same fractionation schedule.

Development of an in silico stochastic 4D model of tumor growth with angiogenesis

Purpose A stochastic computer model of tumour growth with spatial and temporal components that includes tumour angiogenesis was developed. In the current work it was used to simulate head and neck tumour growth. The model also provides the foundation for a 4D cellular radiotherapy simulation tool. Methods The model, developed in Matlab, contains cell positions randomised in 3D space without overlap. Blood vessels are represented by strings of blood vessel units which branch outwards to achieve the desired tumour relative vascular volume. Hypoxic cells have an increased cell cycle time and become quiescent at oxygen tensions less than 1 mmHg. Necrotic cells are resorbed. A hierarchy of stem cells, transit cells and differentiated cells is considered along with differentiated cell loss. Model parameters include the relative vascular volume (2–10%), blood oxygenation (20–100 mmHg), distance from vessels to the onset of necrosis (80–300 μm) and probability for stem cells to undergo symmetric division (2%). Simulations were performed to observe the effects of hypoxia on tumour growth rate for head and neck cancers. Simulations were run on a supercomputer with eligible parts running in parallel on 12 cores. Results Using biologically plausible model parameters for head and neck cancers, the tumour volume doubling time varied from 45 ± 5 days (n = 3) for well oxygenated tumours to 87 ± 5 days (n = 3) for severely hypoxic tumours. Conclusions The main achievements of the current model were randomised cell positions and the connected vasculature structure between the cells. These developments will also be beneficial when irradiating the simulated tumours using Monte Carlo track structure methods.

Simulation of head and neck cancer oxygenation and doubling time in a 4D cellular model with angiogenesis

Tumor oxygenation has been correlated with treatment outcome for radiotherapy. In this work, the dependence of tumor oxygenation on tumor vascularity and blood oxygenation was determined quantitatively in a 4D stochastic computational model of head and neck squamous cell carcinoma (HNSCC) tumor growth and angiogenesis. Additionally, the impacts of the tumor oxygenation and the cancer stem cell (CSC) symmetric division probability on the tumor volume doubling time and the proportion of CSCs in the tumor were also quantified. Clinically relevant vascularities and blood oxygenations for HNSCC yielded tumor oxygenations in agreement with clinical data for HNSCC. The doubling time varied by a factor of 3 from well oxygenated tumors to the most severely hypoxic tumors of HNSCC. To obtain the doubling times and CSC proportions clinically observed in HNSCC, the model predicts a CSC symmetric division probability of approximately 2% before treatment. To obtain the doubling times clinically observed during treatment when accelerated repopulation is occurring, the model predicts a CSC symmetric division probability of approximately 50%, which also results in CSC proportions of 30–35% during this time.