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

Monte Carlo Simulations in Nanomedicine: Advancing Cancer Imaging and Therapy

Monte Carlo (MC) simulations have become important in advancing nanoparticle (NP)-based applications for cancer imaging and therapy. This review explores the critical role of MC simulations in modeling complex biological interactions, optimizing NP designs, and enhancing the precision of therapeutic and diagnostic strategies. Key findings highlight the ability of MC simulations to predict NP bio-distribution, radiation dosimetry, and treatment efficacy, providing a robust framework for addressing the stochastic nature of biological systems. Despite their contributions, MC simulations face challenges such as modeling biological complexity, computational demands, and the scarcity of reliable nanoscale data. However, emerging technologies, including hybrid modeling approaches, high-performance computing, and quantum simulation, are poised to overcome these limitations. Furthermore, novel advancements such as FLASH radiotherapy, multifunctional NPs, and patient-specific data integration are expanding the capabilities and clinical relevance of MC simulations. This topical review underscores the transformative potential of MC simulations in bridging fundamental research and clinical translation. By facilitating personalized nanomedicine and streamlining regulatory and clinical trial processes, MC simulations offer a pathway toward more effective, tailored, and accessible cancer treatments. The continued evolution of simulation techniques, driven by interdisciplinary collaboration and technological innovation, ensures that MC simulations will remain at the forefront of nanomedicine's progress.

Modelling radiobiology

Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy-from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.

Opportunities in Cancer Therapies: Deciphering the Role of Cancer Stem Cells in Tumour Repopulation

Tumour repopulation during treatment is a well acknowledged yet still challenging aspect of cancer management. The latest research results show clear evidence towards the existence of cancer stem cells (CSCs) that are responsible for tumour repopulation, dissemination, and distant metastases in most solid cancers. Cancer stem cell quiescence and the loss of asymmetrical division are two powerful mechanisms behind repopulation. Another important aspect in the context of cancer stem cells is cell plasticity, which was shown to be triggered during fractionated radiotherapy, leading to cell dedifferentiation and thus reactivation of stem-like properties. Repopulation during treatment is not limited to radiotherapy, as there is clinical proof for repopulation mechanisms to be activated through other conventional treatment techniques, such as chemotherapy. The dynamic nature of stem-like cancer cells often elicits resistance to treatment by escaping drug-induced cell death. The aims of this scoping review are (1) to describe the main mechanisms used by cancer stem cells to initiate tumour repopulation during therapy; (2) to present clinical evidence for tumour repopulation during radio- and chemotherapy; (3) to illustrate current trends in the identification of CSCs using specific imaging techniques; and (4) to highlight novel technologies that show potential in the eradication of CSCs.

Assessing the therapeutic response of tumors to hypoxia-targeted prodrugs with an in silico approach

Tumor hypoxia is commonly recognized as a condition stimulating the progress of the aggressive phenotype of tumor cells. Hypoxic tumor cells inhibit the delivery of cytotoxic drugs, causing hypoxic areas to receive insufficient amounts of anticancer agents, which results in adverse treatment responses. Being such an obstruction to conventional therapies for cancer, hypoxia might be considered a target to facilitate the efficacy of treatments in the resistive environment of tumor sites. In this regard, benefiting from prodrugs that selectively target hypoxic regions remains an effective approach. Additionally, combining hypoxia-activated prodrugs (HAPs) with conventional chemotherapeutic drugs has been used as a promising strategy to eradicate hypoxic cells. However, determining the appropriate sequencing and scheduling of the combination therapy is also of great importance in obtaining favorable results in anticancer therapy. Here, benefiting from a modeling approach, we study the efficacy of HAPs in combination with chemotherapeutic drugs on tumor growth and the treatment response. Different treatment schedules have been investigated to see the importance of determining the optimal schedule in combination therapy. The effectiveness of HAPs in varying hypoxic conditions has also been explored in the study. The model provides qualitative conclusions about the treatment response, as the maximal benefit is obtained from combination therapy with greater cell death for highly hypoxic tumors. It has also been observed that the antitumor effects of HAPs show a hypoxia-dependent profile.

Development of a Dual Drug-Loaded, Surfactant-Stabilized Contrast Agent Containing Oxygen

Co-delivery of cancer therapeutics improves efficacy and encourages synergy, but delivery faces challenges, including multidrug resistance and spatiotemporal distribution of therapeutics. To address these, we added paclitaxel to previously developed acoustically labile, oxygen-core, surfactant-stabilized microbubbles encapsulating lonidamine, with the aim of developing an agent containing both a therapeutic gas and two drugs acting in combination. Upon comparison of unloaded, single-loaded, and dual-loaded microbubbles, size (~1.7 µm) and yield (~2 × 10⁹ microbubbles/mL) (~1.7) were not statistically different, nor were acoustic properties (maximum in vitro enhancements roughly 18 dB, in vitro enhancements roughly 18 dB). Both drugs encapsulated above required doses calculated for head and neck squamous cell carcinoma, the cancer of choice. Interestingly, paclitaxel encapsulation efficiency increased from 1.66% to 3.48% when lonidamine was included. During preparation, the combination of single drug-loaded micelles gave higher encapsulation (µg drug/g microbubbles) than micelles loaded with either drug alone (lonidamine, 104.85 ± 22.87 vs. 87.54 ± 16.41), paclitaxel (187.35 ± 8.38 vs. 136.51 ± 30.66). In vivo intravenous microbubbles produced prompt ultrasound enhancement within tumors lasting 3–5 min, indicating penetration into tumor vasculature. The ability to locally destroy the microbubble within the tumor vasculature was confirmed using a series of higher intensity ultrasound pulses. This ability to locally destroy microbubbles shows therapeutic promise that warrants further investigation.

MS-275 (Entinostat) Promotes Radio-Sensitivity in PAX3-FOXO1 Rhabdomyosarcoma Cells

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. About 25% of RMS expresses fusion oncoproteins such as PAX3/PAX7-FOXO1 (fusion-positive, FP) while fusion-negative (FN)-RMS harbors RAS mutations. Radiotherapy (RT) plays a crucial role in local control but metastatic RMS is often radio-resistant. HDAC inhibitors (HDACi) radio-sensitize different cancer cells types. Thus, we evaluated MS-275 (Entinostat), a Class I and IV HDACi, in combination with RT on RMS cells in vitro and in vivo. MS-275 reversibly hampered cell survival in vitro in FN-RMS RD (RASmut) and irreversibly in FP-RMS RH30 cell lines down-regulating cyclin A, B, and D1, up-regulating p21 and p27 and reducing ERKs activity, and c-Myc expression in RD and PI3K/Akt/mTOR activity and N-Myc expression in RH30 cells. Further, MS-275 and RT combination reduced colony formation ability of RH30 cells. In both cell lines, co-treatment increased DNA damage repair inhibition and reactive oxygen species formation, down-regulated NRF2, SOD, CAT and GPx4 anti-oxidant genes and improved RT ability to induce G2 growth arrest. MS-275 inhibited in vivo growth of RH30 cells and completely prevented the growth of RT-unresponsive RH30 xenografts when combined with radiation. Thus, MS-275 could be considered as a radio-sensitizing agent for the treatment of intrinsically radio-resistant PAX3-FOXO1 RMS.

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.

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.

Studying the regression profiles of cervical tumours during radiotherapy treatment using a patient-specific multiscale model

Apart from offering insight into the biomechanisms involved in cancer, many recent mathematical modeling efforts aspire to the ultimate goal of clinical translation, wherein models are designed to be used in the future as clinical decision support systems in the patient-individualized context. Most significant challenges are the integration of multiscale biodata and the patient-specific model parameterization. A central aim of this study was the design of a clinically-relevant parameterization methodology for a patient-specific computational model of cervical cancer response to radiotherapy treatment with concomitant cisplatin, built around a tumour features-based search of the parameter space. Additionally, a methodological framework for the predictive use of the model was designed, including a scoring method to quantitatively reflect the similarity and bilateral predictive ability of any two tumours in terms of their regression profile. The methodology was applied to the datasets of eight patients. Tumour scenarios in accordance with the available longitudinal data have been determined. Predictive investigations identified three patient cases, anyone of which can be used to predict the volumetric evolution throughout therapy of the tumours of the other two with very good results. Our observations show that the presented approach is promising in quantifiably differentiating tumours with distinct regression profiles.

Accelerated vs. conventionally fractionated adjuvant radiotherapy in high-risk head and neck cancer: a meta-analysis

Background

Adjuvant radiotherapy in advanced head and neck squamous cell cancer (HNSCC) reduces the risk of local-regional failure and most likely increases the survival rate. Patients at high risk for tumor recurrence may benefit from more aggressive altered fractionation schedules in order to reduce the overall time from surgery to completion of radiotherapy. Here, we reviewed the results of six randomized trials addressing the above hypothesis.

Methods

In the six trials of interest, a total of 988 patients with locally advanced HNSCC were randomly assigned to receive either accelerated or conventionally fractionated adjuvant radiotherapy. Hazard ratios (HR) were extracted from available publications for local-regional control, distant metastasis as well as overall-, cancer specific- and disease-free survival. Meta-analysis of the effect sizes was performed using fixed and random effect models. Acute and late side effects were categorized and summarized for comparison.

Results

Accelerated radiotherapy did not improve the loco-regional control (n = 988, HR = 0.740, CI = 0.48–1.13, p = 0.162), progression-free survival (HR = 0.89, CI = 0.76–1.04, p = 0.132) or overall survival (HR = 0.88, CI = 0.75–1.04, p = 0.148) significantly. Acute confluent mucositis occurred with significant higher frequency with accelerated radiotherapy. Late side effects did not differ significantly in either group.

Conclusion

Accelerated radiotherapy does not result in a significant improvement of loco-regional control or overall survival in high-risk patients. Acute but not late radiation toxicity were more frequent with the accelerated RT technique. In clinical practice accelerated postoperative radiation therapy might be a suitable option only for a subset of patients.

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.

MicroRNA‑210 negatively regulates the radiosensitivity of nasopharyngeal carcinoma cells

Radiotherapy is one of the primary methods of treatment of malignant tumors, however, resistance to radiation is a major problem. The reasons for the radioresistance are still poorly understood. However, it is generally accepted that microRNAs (miRNAs or miRs) can regulate the radiosensitivity of tumors. The present study therefore aimed to identify specific miRNAs and their effects on radioresistant cells. More specifically, the aim was to investigate specific miRNAs and their effects on radioresistant tumor cells. The radioresistant tumor cells (CNE‑2R) were established using a dose gradient method, and the miRNA expression profiles of CNE‑2R cells and the parental cells (CNE‑2) were determined. The expression of miR‑210 in CNE‑2R cells was significantly higher than in CNE‑2 cells. CNE‑2R cells were transfected with LV‑hsa‑miR‑210‑inhibitor, and CNE‑2 cells were transfected with LV‑hsa‑miR‑210. The expression of miR‑210 was confirmed by reverse transcription quantitative‑polymerase chain reaction. The percentages of CNE‑2R‑miR‑210‑inhibitor and CNE‑2 cells in the G2/M phase were higher than in the CNE‑2R and CNE‑2‑miR‑210 cells, and the percentages of cells in S phase were lower than in the CNE‑2R and CNE‑2‑miR‑210 cells. Following 4 Gy of radiation, CNE‑2R‑miR‑210‑inhibitor and CNE‑2 cells, which express low levels of miR‑210, had a higher apoptosis rate than CNE‑2R and CNE‑2‑miR‑210 cells. Following 4, 8 and 12 Gy of radiation, cell viability and survival fraction of CNE‑2R‑miR‑210‑inhibitor cells were lower than those of CNE‑2R and CNE‑2‑miR‑210 cells, and similar to those of CNE‑2 cells. Together, these findings strongly suggest that miR‑210 negatively regulates the radiosensitivity of tumor cells, and may therefore have therapeutic potential for the treatment of radiation resistance.

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.

Tumour repopulation and the role of abortive division in squamous cell carcinomas during chemotherapy

OBJECTIVES

In head and neck cancers, tumour cell repopulation during chemotherapy is one reason for treatment failure. Some of the mechanisms responsible for this repopulation are cell recruitment and abortive division. Due to lack of quantitative data in the literature regarding these mechanisms, the aim of this study was to investigate the interplay between recruitment and abortive division during cisplatin chemotherapy and to quantify the impact of these mechanisms on tumour control.

MATERIALS AND METHODS

An in silico Monte Carlo tumour model was developed to simulate tumour behaviour during chemotherapy. The virtual tumour had the composition and kinetic properties of a biological tumour. Effect of cisplatin on cell cycle and repopulation mechanisms were simulated and interpreted.

RESULTS

Abortive division contributed to cell production within the tumour during chemotherapy. There was a strong relationship between recruitment and tumour growth due to abortive division. This observation was supported by the value of proliferative/stem ratio, which increased from 1.3 to 36, even when using small recruitment parameters.

CONCLUSIONS

While abortive division contributed towards tumour repopulation during chemotherapy, this mechanism could be controlled by daily doses of cisplatin. On the other hand, stem cells require an additional cytotoxic agent to overcome repopulation due to cell recruitment. Consequently, repopulation via abortive division during chemotherapy did not entail alterations in treatment schedule, nor dose escalation, to control the tumour.

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.

Compensability index for compensation radiotherapy after treatment interruptions

BACKGROUND

The goal of our work was to develop a simple method to evaluate a compensation treatment after unplanned treatment interruptions with respect to their tumour- and normal tissue effect.

METHODS

We developed a software tool in java programming language based on existing recommendations to compensate for treatment interruptions. In order to express and visualize the deviations from the originally planned tumour and normal tissue effects we defined the compensability index.

RESULTS

The compensability index represents an evaluation of the suitability of compensatory radiotherapy in a single number based on the number of days used for compensation and the preference of preserving the originally planned tumour effect or not exceeding the originally planned normal tissue effect. An automated tool provides a method for quick evaluation of compensation treatments.

CONCLUSIONS

The compensability index calculation may serve as a decision support system based on existing and established recommendations.

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.

Influence of stem-cell cycle time on accelerated re-population during radiotherapy in head and neck cancer

OBJECTIVES

Tumour re-population during radiotherapy was identified as an important reason for treatment failure in head and neck cancers. The process of re-population is suggested to be caused by various mechanisms, one of the most plausible one being accelerated division of stem-cells (i.e. drastic shortening of cell cycle duration). However, the literature lacks quantitative data regarding the length of tumour stem-cell cycle time during irradiation.

MATERIALS AND METHODS

The presented work suggests that if accelerated stem-cell division is indeed a key mechanism behind tumour re-population, the stem-cell cycle time can drop below 10 h during radiotherapy. To illustrate the possible implications, the mechanism of accelerated division was implemented into a Monte Carlo model of tumour growth and response to radiotherapy. Tumour response to radiotherapy was simulated with different stem-cell cycle times (between 2 and 10 h) after the initiation of radiotherapy.

RESULTS

It was found that very short stem-cell cycle times lead to tumour re-population during treatment, which cannot be overcome by radiation-induced cell kill. Increasing the number of radiation dose fractions per week might be effective, but only for longer cell cycle times.

CONCLUSION

It is of crucial importance to quantitatively assess the mechanisms responsible for tumour re-population, given that conventional treatment regimens are not efficient in delivering lethal doses to advanced head and neck tumours.

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 role in radiobiological modelling of radiotherapy outcomes

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.