Realizing a new paradigm in radiation therapy treatment planning

This thesis investigates the feasibility of a new IMRT planning paradigm called Interactive Dose Shaping (IDS). The IDS paradigm enables the therapist to directly impose local dose features into the therapy plan. In contrast to the conventional IMRT planning approach, IDS does not employ an objective function to drive an iterative optimization procedure. In the first part of this work, the conventional IMRT plan optimization method is investigated. Concepts for a near-optimal implementation of the planning problem are provided. The second part of this work introduces the IDS concept. It is designed to overcome clinical drawbacks of the conventional method on the one hand and to provide interactive planning strategies which exploit the full potential of modern high-performance computer hardware on the other hand. The realization of the IDS concept consists of three main parts. (1)A two-step Dose Variation and Recovery (DVR) strategy which imposes localized plan features and recovers for unintentional plan modifications elsewhere. (2)A new dose calculation method (3)The design of an IDS planning framework which provides a powerful graphical user interface. It could be shown that the IDS paradigm is able to reproduce conventionally optimized therapy plans and that the IDS concepts can be realized in real-time

A cellular automaton model for spheroid response to radiation and hyperthermia treatments.

Thermo-radiosensitisation is a promising approach for treatment of radio-resistant tumours such as those containing hypoxic subregions. Response prediction and treatment planning should account for tumour response heterogeneity, e.g. due to microenvironmental factors, and quantification of the biological effects induced. 3D tumour spheroids provide a physiological in vitro model of tumour response and a systems oncology framework for simulating spheroid response to radiation and hyperthermia is presented. Using a cellular automaton model, 3D oxygen diffusion, delivery of radiation and/or hyperthermia were simulated for many ([Formula: see text]) individual cells forming a spheroid. The iterative oxygen diffusion model was compared to an analytical oxygenation model and simulations were calibrated and validated against experimental data for irradiated (0-10 Gy) and/or heated (0-240 CEM43) HCT116 spheroids. Despite comparable clonogenic survival, spheroid growth differed significantly following radiation or hyperthermia. This dynamic response was described well by the simulation ([Formula: see text] > 0.85). Heat-induced cell death was implemented as a fast, proliferation-independent process, allowing reoxygenation and repopulation, whereas radiation was modelled as proliferation-dependent mitotic catastrophe. This framework stands out both through its experimental validation and its novel ability to predict spheroid response to multimodality treatment. It provides a good description of response where biological dose-weighting based on clonogenic survival alone was insufficient

Large Eddy Simulations for Dispersed bubbly Flows

In this paper we present detailed Euler-Euler Large Eddy Simulations (LES) of dispersed bubbly flow in a rectangular bubble column. The motivation of this study is to investigate potential of this approach for the prediction of bubbly flows, in terms of mean quantities. The set of physical models describing the momentum exchange between the phases was chosen according to previous experiences of the authors. Experimental data, Euler-Lagrange LES and unsteady Euler-Euler Reynolds-Averaged Navier-Stokes model are used for comparison. It was found that the presented modelling combination provides good agreement with experimental data for the mean flow and liquid velocity fluctuations. The energy spectrum made from the resolved velocity from Euler-Euler LES is presented and discussed

Beam selection for stereotactic ablative radiotherapy using Cyberknife with multileaf collimation.

The Cyberknife system (Accuray Inc., Sunnyvale, CA) enables radiotherapy using stereotactic ablative body radiotherapy (SABR) with a large number of non-coplanar beam orientations. Recently, a multileaf collimator has also been available to allow flexibility in field shaping. This work aims to evaluate the quality of treatment plans obtainable with the multileaf collimator. Specifically, the aim is to find a subset of beam orientations from a predetermined set of candidate directions, such that the treatment quality is maintained but the treatment time is reduced. An evolutionary algorithm is used to successively refine a randomly selected starting set of beam orientations. By using an efficient computational framework, clinically useful solutions can be found in several hours. It is found that 15 beam orientations are able to provide treatment quality which approaches that of the candidate beam set of 110 beam orientations, but with approximately half of the estimated treatment time. Choice of an efficient subset of beam orientations offers the possibility to improve the patient experience and maximise the number of patients treated

Towards real-time photon Monte Carlo dose calculation in the cloud.

Near real-time application of Monte Carlo (MC) dose calculation in clinic and research is hindered by the long computational runtimes of established software. Currently, fast MC software solutions are available utilising accelerators such as graphical processing units (GPUs) or clusters based on central processing units (CPUs). Both platforms are expensive in terms of purchase costs and maintenance and, in case of the GPU, provide only limited scalability. In this work we propose a cloud-based MC solution, which offers high scalability of accurate photon dose calculations. The MC simulations run on a private virtual supercomputer that is formed in the cloud. Computational resources can be provisioned dynamically at low cost without upfront investment in expensive hardware. A client-server software solution has been developed which controls the simulations and transports data to and from the cloud efficiently and securely. The client application integrates seamlessly into a treatment planning system. It runs the MC simulation workflow automatically and securely exchanges simulation data with the server side application that controls the virtual supercomputer. Advanced encryption standards were used to add an additional security layer, which encrypts and decrypts patient data on-the-fly at the processor register level. We could show that our cloud-based MC framework enables near real-time dose computation. It delivers excellent linear scaling for high-resolution datasets with absolute runtimes of 1.1 seconds to 10.9 seconds for simulating a clinical prostate and liver case up to 1% statistical uncertainty. The computation runtimes include the transportation of data to and from the cloud as well as process scheduling and synchronisation overhead. Cloud-based MC simulations offer a fast, affordable and easily accessible alternative for near real-time accurate dose calculations to currently used GPU or cluster solutions

Bubble aspect ratio in dense bubbly flows: Experimental studies in low Morton-number systems

Almost every modelling approach of bubbly flows includes assumptions concerning the bubble shape. Such assumptions are usually made based on single bubble experiments in quiescent flows, which is far away from the flow field observed in large-scale multiphase facilities. Considering low Morton-numbers and the highly deformable interface at medium and large Eötvös-numbers, the evaluation of the bubble shape in such systems under real flow conditions is highly desirable. In this study, we experimentally evaluate the bubble shape (in terms of aspect ratio), at low Morton-numbers, in different bubble column setups and a pipe flow setup under different operating conditions. The bubble shape in the bubble column experiments were obtained with cameras at Politecnico di Milano and Helmholtz-Zentrum Dresden Rossendorf (HZDR) whereas the shapes in the pipe flows were measured by the ultrafast electron beam X-ray tomography system (ROFEX) at HZDR. In the bubble column experiments almost the same shape is observed; conversely, the shape in the pipe flows distinctly depends on the flow conditions. In conclusion, in bubble columns the assumption of a constant shape regardless of the flow conditions is valid whereas in pipe flows the turbulence and shear rates can be strong enough to deform distinctly the bubbles

Multiobjective navigation of external radiotherapy plans based on clinical criteria

This study considers a navigation method for finding the most preferable radiotherapy plan from a discrete set using planner-defined clinical criteria. The method is based on repeatedly solving an optimisation model to identify a plan that best satisfies the aspiration values set by the planner. During navigation, the planner iteratively adjusts the aspiration values to match the preference information learned from previous plans until the most preferable plan is identified. The use of soft constraints to model aspiration values enables navigation among a discrete set and allows the planner to freely specify the aspiration values without producing an infeasible model. We demonstrate the use of the model by applying it to a prostate cancer case. This illustrates that improvements in optimisation criteria do not necessarily lead to improvements in clinical criteria. Hence the method obviates the need to simultaneously monitor both optimisation and clinical criteria in current navigation systems. Instead, the direct use of clinical criteria for navigation aids the planner to quickly identify the most preferable plan

Combining radiation with hyperthermia: a multiscale model informed by in vitro experiments

Funding: Cancer Research UK. Research at The Institute of Cancer Research is supported by Cancer Research UK under Programme C33589/A19727. Peter Ziegenhein is supported by Cancer Research UK under Programme C33589/A19908.Combined radiotherapy and hyperthermia offer great potential for the successful treatment of radio-resistant tumours through thermo-radiosensitization. Tumour response heterogeneity, due to intrinsic, or micro-environmentally induced factors, may greatly influence treatment outcome, but is difficult to account for using traditional treatment planning approaches. Systems oncology simulation, using mathematical models designed to predict tumour growth and treatment response, provides a powerful tool for analysis and optimization of combined treatments. We present a framework that simulates such combination treatments on a cellular level. This multiscale hybrid cellular automaton simulates large cell populations (up to 107 cells) in vitro, while allowing individual cell-cycle progression, and treatment response by modelling radiation-induced mitotic cell death, and immediate cell kill in response to heating. Based on a calibration using a number of experimental growth, cell cycle and survival datasets for HCT116 cells, model predictions agreed well (R2 > 0.95) with experimental data within the range of (thermal and radiation) doses tested (0–40 CEM43, 0–5 Gy). The proposed framework offers flexibility for modelling multimodality treatment combinations in different scenarios. It may therefore provide an important step towards the modelling of personalized therapies using a virtual patient tumour.Publisher PDFPeer reviewe