[en] In this paper, models are described which have been developed to model both the way in which a population of cells respond to radiation and the way in which a population of patients respond to radiotherapy to assist the conduct of clinical trials in silico. Population balance techniques have been used to simulate the age distribution of tumour cells in the cell cycle. Sensitivity to radiation is not constant round the cell cycle and a single fraction of radiation changes the age distribution. Careful timing of further fractions of radiation can be used to maximize the damage delivered to the tumour while minimizing damage to normal tissue. However, tumour modelling does not necessarily predict patient outcome. A separate model has been established to predict the course of a brain cancer called glioblastoma multiforme (GBM). The model considers the growth of the tumour and its effect on the normal brain. A simple representation is included of the health status of the patient and hence the type of treatment offered. It is concluded that although these and similar models have a long way yet to be developed, they are beginning to have an impact on the development of clinical practice

[en] Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of 'general Markov models', providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy and argue that the proposed method can automate the creation of Markov models from existing data. The approach has the potential to support the radiotherapy community in conducting systematic analyses involving predictive modelling of existing and upcoming radiotherapy data. We expect it to facilitate the application of modelling techniques in medical decision problems beyond the field of radiotherapy, and to improve the comparability of their results. (author)

[en] The aim of this study is to develop a mathematical modelling method that can predict individual patients’ response to radiotherapy, in terms of tumour volume change during the treatment. The main concept is to start from a population-average model, which is subsequently updated from an individual’s tumour volume measurement. The model becomes increasingly personalised and so too does the prediction it produces. This idea of adaptive prediction was realised by using a Bayesian approach for updating the model parameters. The feasibility of the developed method was demonstrated on the data from 25 non-small cell lung cancer patients treated with helical tomotherapy, during which tumour volume was measured from daily imaging as part of the image-guided radiotherapy. The method could provide useful information for adaptive treatment planning and dose scheduling based on the patient’s personalised response. (paper)

[en] This paper reports a modelling study of tumour volume dynamics in response to stereotactic ablative radiotherapy (SABR). The main objective was to develop a model that is adequate to describe tumour volume change measured during SABR, and at the same time is not excessively complex as lacking support from clinical data. To this end, various modelling options were explored, and a rigorous statistical method, the Akaike information criterion, was used to help determine a trade-off between model accuracy and complexity. The models were calibrated to the data from 11 non-small cell lung cancer patients treated with SABR. The results showed that it is feasible to model the tumour volume dynamics during SABR, opening up the potential for using such models in a clinical environment in the future. (paper)

[en] Highlights: • Temporal aspects of clinical FLASH delivery. • Possible effects of fractionated FLASH dosimetry. • Examining the initial clinical applications. • Extension of clinical studies required to demonstrate normal tissue sparing.

[en] The cytotoxicity of radiotherapy and chemotherapy can be enhanced by modulating DNA repair. PARP is a family of enzymes required for an efficient base-excision repair of DNA single-strand breaks and inhibition of PARP can prevent the repair of these lesions. The current study investigates the trimodal combination of ABT-888, a potent inhibitor of PARP1-2, ionizing radiation and temozolomide(TMZ)-based chemotherapy in glioblastoma (GBM) cells. Four human GBM cell lines were treated for 5 h with 5 μM ABT-888 before being exposed to X-rays concurrently with TMZ at doses of 5 or 10 μM for 2 h. ABT-888"′s PARP inhibition was measured using immunodetection of poly(ADP-ribose) (pADPr). Cell survival and the different cell death pathways were examined via clonogenic assay and morphological characterization of the cell and cell nucleus. Combining ABT-888 with radiation yielded enhanced cell killing in all four cell lines, as demonstrated by a sensitizer enhancement ratio at 50% survival (SER_5_0) ranging between 1.12 and 1.37. Radio- and chemo-sensitization was further enhanced when ABT-888 was combined with both X-rays and TMZ in the O"6-methylguanine-DNA-methyltransferase (MGMT)-methylated cell lines with a SER_5_0 up to 1.44. This effect was also measured in one of the MGMT-unmethylated cell lines with a SER_5_0 value of 1.30. Apoptosis induction by ABT-888, TMZ and X-rays was also considered and the effect of ABT-888 on the number of apoptotic cells was noticeable at later time points. In addition, this work showed that ABT-888 mediated sensitization is replication dependent, thus demonstrating that this effect might be more pronounced in tumour cells in which endogenous replication lesions are present in a larger proportion than in normal cells. This study suggests that ABT-888 has the clinical potential to enhance the current standard treatment for GBM, in combination with conventional chemo-radiotherapy. Interestingly, our results suggest that the use of PARP inhibitors might be clinically significant in those patients whose tumour is MGMT-unmethylated and currently derive less benefit from TMZ

[en] A new initiative to build a vertical scanning focussed nanobeam is outlined. This is a collaboration between the Gray Cancer Institute and University of Surrey. The new beam line will operate in both single ion and full current modes and will enable the irradiation of single cells in vitro with precisely counted numbers of ions, it will also enable the analysis of cells in vitro. The beam will be focussed and scanned and should be capable of irradiating 100,000 cells per hour. A new end station will enable the cells to be irradiated in an environmentally controlled environment and will enable the cells to be imaged both on-line and off-line. The beam line will be housed in its own purpose built building, with the area around the end station comprising a biological clean room

[en] SummaryIn this study, we used evidence-based mathematical modelling to predict the patient cohort for MR-linac to assess its feasibility in a time of austerity. We discuss our results and the implications of evidence-based radiotherapy demand modelling tools such as Malthus on the implementation of new technology and value-based healthcare.