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

Predictive modeling of hypoxic head and neck cancers during fractionated radiotherapy with gold nanoparticle radiosensitization

PURPOSE

Intrinsic radioresistance and increased proliferation rates in head and neck cancers (HNCs) are associated with negative radiotherapy (RT) treatment responses. The use of gold nanoparticles (AuNPs) as radiosensitizers could enable total radiation dose reduction and lowered radiation toxicity. AuNP radiosensitization may overcome hypoxia-induced radioresistance and treatment-induced accelerated repopulation of cancer cells in HNCs, improving radiotherapy outcomes.

METHODS

Tumor control was determined by considering individual cancer cell responses in probabilistic computational simulations using HYP-RT software for clinical radiotherapy doses and fractionation schedules along with three different nanoparticle administration schedules. Antagonistic tumor hypoxia and rapid tumor regrowth due to accelerated repopulation of cancers cells were taken into consideration.

RESULTS

Simulations indicate that tumors that are conventionally uncontrollable can be controlled with AuNP radiosensitization. In simulations where the absence of AuNPs required radiotherapy doses above standard clinical prescriptions, reoccurring AuNP administration allowed for radiation dose reductions below standard clinical dose prescriptions. For example, considering a 2 Gy per fraction radiotherapy schedule, tumor control was achieved with 57.2 ± 5.1 Gy (P = <0.0001) for weekly AuNP administration and 53.0 ± 4.0 Gy (P = <0.0001) for biweekly AuNP administration compared to 69.9 ± 5.8 Gy with no radiosensitization.

CONCLUSIONS

AuNPs decreased the predicted RT total doses required to achieve tumor control via total stem cell elimination, offering an optimistic prediction and method for which hypoxia-induced and rapidly growing radioresistant tumors are treated more effectively. Outcomes are also shown to be sensitive to the RT schedule with data for hyperfractionated RT indicating the greatest benefits from radiosensitization.

In silico modeling of cellular probabilistic nanoparticle radiosensitization in head and neck cancers

Background: The use of gold nanoparticles (AuNPs) as radiosensitizers may offer a new approach in the treatment of head and neck cancers; minimizing treatment-associated toxicities and improving patient outcomes. AuNPs promote localized dose deposition; permitting improved local control and/or dose reduction. Aim: This work aimed to address the theoretical optimization of radiation doses, fractionation and nanoparticle injection schedules to maximize therapeutic benefits. Materials & methods: Probabilistic nanoparticle sensitization factors were incorporated into the individual cell-based HYP-RT computer model of tumor growth and radiotherapy. Results: Total dose outcomes across all radiation therapy treatment regimens were found to be significantly reduced with the presence of AuNPs, with bi-weekly injections showing the most decrease. Conclusion: Outcomes suggest the need for regular AuNP administration to permit effective radiosensitization.

Radiobiologically derived biphasic fractionation schemes to overcome the effects of tumour hypoxia

OBJECTIVE

As a fractionated course of radiotherapy proceeds tumour shrinkage leads to resolution of hypoxia and the initiation of accelerated proliferation of radioresistant cancer cells with better repair capacity. We hypothesise that, in tumours with significant hypoxia, improved tumour control could be achieved with biphasic fractionation schedules that either use acceleration after 3-4 weeks of conventional radiotherapy or deliver a higher proportional dose towards the end of a course of treatment. We conducted a modelling study based on the concept of biological effective dose (BED) comparing such novel regimens with conventional fractionation.

METHODS

The comparator conventional fractionation schedule 70 Gy in 35 fractions delivered over 7 weeks was tested against the following novel regimens, both of which were designed to be isoeffective in terms of late normal tissue toxicity.40 Gy in 20 fractions over 4 weeks followed by 22.32 Gy in 6 consecutive daily fractions (delayed acceleration)30.4 Gy in 27 fractions over 4 weeks followed by 40 Gy in 15 fractions over 3 weeks (temporal dose redistribution)The delayed acceleration regimen is exactly identical to that of the comparator schedule over the first 28 days and the BED gains with the novel schedule are achieved during the second phase of treatment when reoxygenation is complete. For the temporal redistribution regimen, it was assumed that the reoxygenation fraction progressively increases during the first 4 weeks of treatment and an iterative approach was used to calculate the final tumour BED for varying hypoxic fractions.

RESULTS

Novel fractionation with delayed acceleration or temporal fractionation results in tumour BED gains equivalent to 3.5-8 Gy when delivered in 2 Gy fractions.

CONCLUSION

In hypoxic tumours, novel fractionation strategies result in significantly higher tumour BED in comparison to conventional fractionation.

ADVANCES IN KNOWLEDGE

We demonstrate that novel biphasic fractionation regimens could overcome the effects of tumour hypoxia resulting in biological dose escalation.

Approaches to combat hypoxia in cancer therapy and the potential for in silico models in their evaluation

AIM

The negative impact of tumour hypoxia on cancer treatment outcome has been long-known, yet there has been little success combating it. This paper investigates the potential role of in silico modelling to help test emerging hypoxia-targeting treatments in cancer therapy.

METHODS

A Medline search was undertaken on the current landscape of in silico models that simulate cancer therapy and evaluate their ability to test hypoxia-targeting treatments. Techniques and treatments to combat tumour hypoxia and their current challenges are also presented.

RESULTS

Hypoxia-targeting treatments include tumour reoxygenation, hypoxic cell radiosensitization with nitroimidazoles, hypoxia-activated prodrugs and molecular targeting. Their main challenges are toxicity and not achieving adequate delivery to hypoxic regions of the tumour. There is promising research toward combining two or more of these techniques. Different types of in silico therapy models have been developed ranging from temporal to spatial and from stochastic to deterministic models. Numerous models have compared the effectiveness of different radiotherapy fractionation schedules for controlling hypoxic tumours. Similarly, models could help identify and optimize new treatments for overcoming hypoxia that utilize novel hypoxia-targeting technology.

CONCLUSION

Current therapy models should attempt to incorporate more sophisticated modelling of tumour angiogenesis/vasculature and vessel perfusion in order to become more useful for testing hypoxia-targeting treatments, which typically rely upon the tumour vasculature for delivery of additional oxygen, (pro)drugs and nanoparticles.

Adapting VMAT plans optimized for an HD120 MLC for delivery with a Millennium MLC

Linac downtime invariably impacts delivery of patients' scheduled treatments. Transferring a patient's treatment to an available linac is a common practice. Transferring a Volumetric Modulated Arc Therapy (VMAT) plan from a linac equipped with a standard‐definition MLC to one equipped with a higher definition MLC is practical and routine in clinics with multiple MLC‐equipped linacs. However, the reverse transfer presents a challenge because the high‐definition MLC aperture shapes must be adapted for delivery with the lower definition device. We have developed an efficient method to adapt VMAT plans originally designed for a high‐definition MLC to a standard‐definition MLC. We present the dosimetric results of our adaptation method for head‐and‐neck, brain, lung, and prostate VMAT plans. The delivery of the adapted plans was verified using standard phantom measurements.

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.