L’imagerie proton est étudiée comme alternative à la tomodensitométrie X pour la planification de traitement en hadronthérapie. En obtenant directement les pouvoirs d’arrêt relatifs des tissus, l’incertitude sur le parcours des particules pourrait être réduite. Un scanner à protons est constitué d’un calorimètre ou d’un détecteur de parcours afin d’obtenir l’information sur l’énergie déposée par chaque proton dans l’objet imagé et de deux ensembles de trajectographes enregistrant la position et direction de chaque particule en amont et en aval de l’objet. Ce travail concerne l’étude des données d’un scanner à protons et l’utilisation possible de toutes les informations enregistrées. Une étude de reconstruction d’image a permis de montrer que les informations sur le taux de transmission et sur la déviation de chaque particule peuvent être utilisées pour produire des images aux propriétés visuelles intéressantes pour le diagnostic. La preuve de concept de la possibilité d’une imagerie quantitative utilisant ces informations est présentée. Ces résultats sont une première étape vers l’imagerie proton utilisant toutes les données enregistrées. / Proton computed tomography is being studied as an alternative to X-ray CT imaging for charged particle therapy treatment planning. By directly mapping the relative stopping power of the tissues, the uncertainty on the range of the particles could be reduced. A proton scanner consists in a calorimeter or range-meter to obtain the information on the energy lost by each proton in the object, as well as two sets of tracking planes to record the position and direction of each particle upstream and downstream from the object. This work concerns the study of the outputs of a proton scanner and the possible use of all the recorded information. A reconstruction study made it possible to show that the information on the transmission rate and on the scattering of each particle can be used to produce images with visual properties that could be of interest for diagnostics. The proof of concept of the possibility of quantitative imaging using this information is also put forward. These results are the first step towards a clinical use of proton imaging with all the recorded data.

Intensity modulated proton therapy (IMPT) in head and neck squamous cell carcinoma (HNSCC) offers superior advantages over conventional photon therapy, by generating high conformal doses to the target volume and improved sparing of the organ at risks (OARs). Besides, robust treatment planning approaches, which account for uncertainties directly into the plan optimization process, are able to generate high quality plans robust against uncertainties compared to a PTV margin expansion approach. During radiation treatment, patients are prone to present anatomical variations during the treatment course, which can be random deviations in patient positioning, as well as treatment-induced tumor shrinkage and patient weight variations. For IMPT plans using a PTV margin expansion, these anatomical variations might disturb the calculated nominal plan, with a decrease to the dose delivered to the target volume and/or increased dose to the OARs above its tolerance, and a plan adaptation might be needed. However, the influence of these anatomical variations in robustly optimized plans for HNSCC entities has not been determined. The first part of this thesis compared two proton therapy methods, single-field optimization (SFO) and multi-field optimization (MFO), applied to the treatment of unilateral HNSCC target volumes, consisting of a cohort of 8 patients. For each method, a PTV-based and a robustly optimized plan were generated, resulting in four plans per patient. The four plans showed adequate target coverage on the nominal plan, with larger doses to the ipsilateral parotid gland for both SFO approaches. No plan showed a clear advantage when variations in the anatomy during the treatment course were considered, and the same was observe considering additional setup and range uncertainties. Hence, no plan showed a decisive superiority regarding plan robustness and potential need of replanning. In the second part of this thesis, an anatomical robustly optimized plan approach was proposed (aRO), which considers additional CT datasets in the plan optimization, representing random non-rigid patient positioning variations. The aRO approach was compared to a classical robustly optimized plan (cRO) and a PTV-based approach for a cohort of 20 bilateral HNSCC patients. PTV-based and cRO approaches were not sufficient to account for weekly anatomical variations, showing a degradation in the target coverage in 10 and 5 of 20 cases, respectively. Conversely, the proposed aRO approach was able to preserve the target coverage in 19 of 20 cases, with only one patient requiring plan adaptation. An extended robustness analysis conducted on both cRO and aRO plan approaches considering weekly anatomical variations, setup and range errors, showed that the variations in anatomy were the most critical variable for loss in target coverage, while setup and range uncertainties played a minor role. The price of the increased plan robustness for the aRO approach was a significant larger integral dose to the healthy tissue, compared to the cRO plan. However, the increase in integral dose was not reflected on the planned dose to the OARs, which were comparable between both plans. Therefore, the price for a superior plan robustness can be considered as low. In the current clinical practice, the implementation of the aRO approach would be able to reduce the need of plan adaptation. For its application, the acquisition of additional planning CT datasets, considering a complete patient repositioning between scans is required, in order to simulate random non-rigid position variations as simulated in this study by the use of the first two weekly cCTs in the plan optimization. Further studies using multiple planning CT acquisition, including strategies to reduce the patient CT dose such as dual-energy CT and iterative reconstruction algorithms, are needed to confirm the presented findings. Additionally, the aRO approach applied to other body sites and entities might also be investigated. In near future, further in-room imaging methods such as cone-beam CT and magnetic resonance imaging, optimized for proton therapy, might be used to acquire additional datasets. Moreover, alternative approaches capable of modeling variations in patient positioning as biomechanical models and deep learning methods might be able to generate in silico additional image datasets for use in proton treatment planning. In summary, this thesis proposes an additional contribution for robust treatment planning in IMPT, with the generation of treatment plans robust against anatomy variations, together with setup and range uncertainties, which can benefit the clinical workflow by reducing the need of plan adaptation.:Contents List of Figures List of Tables List of Abbreviations 1 Introduction 2 Proton Therapy 2.1 Rationale for Proton Therapy 2.2 Beam Delivery Techniques 2.2.1 Passive Scattering 2.2.2 Pencil Beam Scanning 2.3 Uncertainties in Proton Therapy 2.3.1 Target Volume Definition 2.3.2 Range Uncertainty 2.3.3 Setup Uncertainty 2.3.4 Biological Uncertainty 2.3.5 Anatomical Variations 3 Robust Treatment Planning and Robustness Evaluation 3.1 Robust Treatment Planning 3.1.1 Including Uncertainties in the Optimization 3.1.2 Differences Between Approaches 3.2 Robustness Evaluation 3.2.1 Error Scenarios 3.2.2 Visual Evaluation of Plan Robustness 3.2.3 Summary 4 Illustration of Robust Treatment Planning in a Simple Geometry 4.1 Plan Design 4.2 Plan Results 4.2.1 Doses on Nominal Plan 4.2.2 Influence of Uncertainties in Plan Robustness 4.3 Discussion and Conclusion 5 Evaluation of Robust Treatment Plans in Unilateral Head and Neck Squamous Cell Carcinoma 5.1 Study Design 5.1.1 Calculation Parameters 5.1.2 Plan Robustness Evaluation 5.2 Results 5.2.1 Evaluation of Nominal Plan Doses 5.2.2 Evaluation of Plan Robustness Against Uncertainties 5.3 Discussion 5.4 Conclusions 6 Assessment of Anatomical Robustly Optimized Plans in Bilateral Head and Neck Squamous Cell Carcinoma 6.1 Anatomical Robust Optimization 6.2 Study Design 6.2.1 Calculation Parameters 6.2.2 Assessment of Plan Robustness 6.3 Results 6.3.1 Evaluation of Nominal Plan Doses 6.3.2 Evaluation of Plan Robustness Against Uncertainties 6.4 Discussion 6.4.1 Robustness Against Anatomical Variations 6.4.2 Robustness Against Additional Setup and Range Uncertainties 6.4.3 Study Limitations 6.5 Conclusions 7 Summary 8 Zusammenfassung Bibliography Appendix

The radiotherapy clinics in Sweden have been without a functioning national platform consisting of dose data from patients undergoing radiotherapy. A national collaboration between clinics will improve the quality of radiotherapy since clinics will be able to compare dose data from treatment plans between clinics. It will also help and improve future researches in radiotherapy. A new national quality registry for radiotherapy in Sweden is under development and is located on the INCA platform. The aim of this study is to do a quality assurance of the INCA registry. The data stored in the registry are calculated from the treatment plans stored locally at the clinics. The quality assurance of the registry is done by creating a program run by Python code and by using Streamlit as the graphical user interface. The program takes dose and volume data from the dose volume histograms located in treatment plans from the INCA database and compares it with the dose and volume data from the local clinics' treatment planning system. The different treatment planning systems considered in the program are Oncentra(Elekta, Sweden), Eclipse(Varian, U.S.), RayStation(RaySearch Laboratories, Sweden) and Monaco(Electa, Sweden). The compared absorbed doses are the dose to 99% of the structure volume(D99%), D98%, D50%, D2% and D1%. The program generates how much the INCA data differs from the TPS data in percent and is named QARS(Quality Assurance of the Radiotherapy Database in Sweden). A verification of the created program and a preliminary evaluation is done on a limited dataset containing three patient groups(prostate patients, lung patients and head and neck patients) with five patients in each group. The dataset is run through the program with patient data from both Oncentra and Eclipse. The result indicates that all the near-maximum doses, D2% and D1% in INCA are very close to their corresponding TPS dose. There is a more noticeable difference in the near-minimum doses, D99% and D98% but also for some D50% where the difference seems to increase in larger structure volumes with very low doses and in very small structure volumes, smaller than 0.01 cm3. It is compared how well INCA agrees with Oncentra and Eclipse respectively and it is clear that Eclipse has a smaller difference to INCA than Oncentra for structures with very small volumes and larger structures with low doses. To summarise the study, it generates a program for quality assurance of the national quality registry for radiotherapy in Sweden which hopefully can help improve the quality of radiotherapy and help future researches in the field.

Multi-ion radiotherapy has been suggested as a new way to treat cancer, combining the radiological advantages of lighter and heavier ions in a single treatment to improve plan robustness and increase LETd in the target. To succeed, multi-ion radiotherapy requires a treatment planning system capable of computing dose for and optimising multi-ion treatment plans. In this project, prototypical multi-ion radiotherapy treatment planning support has been implemented in the RayStation treatment planning system. The existing dose engine for helium and carbon ion beams has been extended to support protons, oxygen and neon ions, and support has been added for dose computation and plan optimisation for any combination of these ion species. The implemented functionality has been evaluated in two phantom cases and a patient case. Multi-ion treatment plans have been shown to outperform carbon ion treatment plans in terms of simultaneously providing plan robustness, uniform RBE-weighted dose and high LETd. In the patient case, the multi-ion plan displayed significant improvements in the ability to "paint" high LETd in the target. Clinical studies are required to determine to what extent this new modality increases treatment quality in practice.

Treating cancer with radiotherapy requires precise planning. Several planning pipelines rely on reference dose mimicking, where one tries to find machine parameters best mimicking a given reference dose. Dose mimicking relies on having a function that quantifies dose similarity well, necessitating methods for feature extraction of dose images. In this thesis we investigate ways of extracting features from clinical doseimages, and propose a few proof-of-concept dose mimicking functions using the extracted features. We extend current techniques and lay the foundation for new techniques for feature extraction, using mathematical frameworks developed in entirely different areas. In particular we give an introduction to wavelet theory, which provides signal decomposition techniques suitable for analysing local structure, and propose two different dose mimicking functions using wavelets. Furthermore, we extend ROI-based mimicking functions to use artificial ROIs, and we investigate variational autoencoders and their application to the clinical dose feature extraction problem. We conclude that the proposed functions have the potential to address certain shortcomings of current dose mimicking functions. The four methods all seem to approximately capture some notion of dose similarity. Used in combination with the current framework they have the potential of improving dose mimickingresults. However, the numerical tests supporting this are brief, and more thorough numerical investigations are necessary to properly evaluate the usefulness of the new dose mimicking functions. / Behandling av cancer med strålterapi kräver precis planering. Flera olika planeringsramverk bygger på doshärmning, som innebär att hitta de maskinparametrar som bäst härmar en given referensdos. För doshärmning behövs en funktion som kvantifierar likheten mellan två doser, vilket kräver ett sätt att extrahera utmärkande egenskaper – så kallade features – från dosbilder. I det här examensarbetet undersöker vi olika matematiska metoder för att extrahera features från kliniska dosbilder, och presenterar några olika förslag på prototyper till doshärmningsfunktioner, konstruerade utifrån extraherade features. Vi utvidgar nuvarande tekniker och lägger grunden för nya tekniker genom att använda matematiska ramverk utvecklade för helt andra syften. Speciellt så ger vi en introduktion till wavelet-teori, som ger matematiska verktyg för att analysera lokala beteenden hos signaler, exempelvis bilder. Vi föreslår två olika doshärmningsfunktioner som utnyttjar wavelets, och utvidgar ROI-baseraddoshärmning genom att introducera artificiella ROIar. Vidare så undersökervi så kallade variational autoencoders  och möjligheten att använda dessa för extrahering av features från dosbilder. Vi kommer fram till att de föreslagna funktionerna har potential att åtgärda vissa begränsningar som finns hos de doshärmningsfunktioner som används idag. De fyra metoderna verkar alla approximativt kvantifiera begreppet doslikhet. Användning av dessa nya metoder i kombination med nuvarande ramverk för doshärmning har potential att förbättra resultaten från doshärmning. De numeriska undersökningar som underbygger dessa slutsatser är dock inte särskilt ingående, så mer noggranna numeriska tester krävs för att kunna ge några definitiva svar angående de presenterade doshärmningsfunktionernas användbarhet ipraktiken.

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Irreversible electroporation (IRE) is a non-thermal tissue ablation modality in which electrical pulses are used to generate targeted disruption of cellular membranes. Clinically, IRE is administered by inserting one or more needles within or around a region of interest, then applying a series of short, high amplitude pulsed electric fields (PEFs). The treatment effect is dictated by the local field magnitude, which is quite high near the electrodes but dissipates exponentially. When cells are exposed to fields of sufficient strength, nanoscale "pores" form in the membrane, allowing ions and macromolecules to rapidly travel into and out of the cell. If enough pores are generated for a substantial amount of time, cell homeostasis is disrupted beyond recovery and cells eventually die. Due to this unique non-thermal mechanism, IRE generates targeted cell death without injury to extracellular proteins, preserving tissue integrity. Thus, IRE can be used to treat tumors precariously positioned near major vessels, ducts, and nerves. Since its introduction in the late 2000s, IRE has been used successfully to treat thousands of patients with focal, unresectable malignancies of the pancreas, prostate, liver, and kidney. It has also been used to decellularize tissue and is gaining attention as a cardiac ablation technique. Though IRE opened the door to treating previously inoperable tumors, it is not without limitation. One drawback of IRE is that pulse delivery results in intense muscle contractions, which can be painful for patients and causes electrodes to move during treatment. To prevent contractions in the clinic, patients must undergo general anesthesia and temporary pharmacological paralysis. To alleviate these concerns, high-frequency irreversible electroporation (H-FIRE) was introduced. H-FIRE improves upon IRE by substituting the long (~100 µs) monopolar pulses with bursts of short (~1 µs) bipolar pulses. These pulse waveforms substantially reduce the extent of muscle excitation and electrochemical effects. Within a burst, each pulse is separated from its neighboring pulses by a short delay, generally between 1 and 5 µs. Since its introduction, H-FIRE burst waveforms have generally been constructed simply by choosing the duration of constitutive pulses within the burst, with little attention given to this delay. This is quite reasonable, as it has been well documented that pulse duration plays a critical role in determining ablation size. In this dissertation, we explore the role of these latent periods within burst waveforms as well as their interaction with other pulse parameters. Our central hypothesis is that tuning the latent periods will allow for improved ablation size with reduced muscle contractions over traditional waveforms. After gaining a simple understanding of how pulse width and delay interact in vitro, we demonstrate theoretically that careful tuning of the delay within (interphase) and between (interpulse) bipolar pulses in a burst can substantially reduce nerve excitation. We then analyze how pulse duration, polarity, and delays affect the lethality of burst waveforms toward determining the most optimal parameters from a clinical perspective. Knowing that even the most ideal waveform will require slightly increased voltages over what is currently used clinically, we compare the clinical efficacy of two engineered thermal mitigation strategies to determine what probe design modifications will be needed to successfully translate H-FIRE to the clinic while maintaining large, non-thermal ablation volumes. Finally, we translate these findings in two studies. First, we demonstrate that burst waveforms with an improved delay structure allow for enhanced safety and larger ablation volumes in vivo. And finally, we examine the efficacy of H-FIRE in spontaneous canine liver tumors while also comparing the ablative effect of H-FIRE in tumor and non-neoplastic tissue in a veterinary clinical setting. / Doctor of Philosophy / Cancer is soon to become the most common cause of death in the United States. In 2023, approximately 2 million new cases of cancer will be diagnosed, leading to roughly 650 thousand lost lives. Interestingly, about half of newly diagnosed cancers are caught in the early stages before the disease has spread throughout the body. With effective local intervention, these patients could potentially be cured of their malignancy. Surgical removal of the tumor is the gold standard, but it is often not possible due to tumor location, patient comorbidities, or organ health status. In some instances, focal thermal ablation with radiofrequency or microwave energy can be performed when resection is not possible. These treatments entail the delivery of thermal energy through a needle electrode, which causes local tissue damage through coagulation (cooking) of the tissue. However, thermal ablation destroys tissue indiscriminately, meaning that any nearby blood vessels or neural components will also be damaged, which precludes thousands of patients from treatment each year. Irreversible electroporation (IRE) was introduced to overcome these challenges and provide a treatment option for patients diagnosed with otherwise untreatable tumors. IRE uses pulsed electric fields to generate nanoscale pores in cell membranes, which lead to a homeostatic imbalance and cell death. Because IRE is a membrane-based effect, it does not rely on thermal effects to generate cellular injury, which allows it to be administered to tumors that are adjacent to critical tissue structures such as major nerves and vasculature. Though IRE opened the door to treating otherwise inoperable tumors, procedures are technically challenging and require specialized anesthesia protocols. High-frequency irreversible electroporation (H-FIRE) was introduced by our group roughly a decade ago to simplify the procedure through the use of an alternate pulsing strategy. These higher frequency pulses offer several advantages such as limiting muscle contractions and reducing the risk of cardiac interference, both of which were concerns with IRE. However, H-FIRE ablations have been limited in size, and there is limited knowledge regarding the optimal pulsing strategy needed in order to maximize the ratio of therapeutic benefits to undesirable side effects like muscle stimulation and Joule heating. In this dissertation, we sought to understand how different pulse parameters affect these outcomes. Using a combination of computational, benchtop, and in vivo experiments, we comprehensively characterized the behavior of user-tunable pulse parameters and identified optimal methods for constructing H-FIRE protocols. We then translated our findings in a proof-of-principle study to demonstrate the ability of newly introduced waveform designs to increase ablation size with H-FIRE. Overall, this dissertation improves our understanding of how H-FIRE waveform selection affects clinical outcomes, introduces a new strategy for maximizing therapeutic outcomes with minimal side effects, and provides a framework for selecting parameters for specific applications.

Proton radiotherapy is a cancer treatment which has the potential to offer greater cure rates and/or fewer serious side effects than conventional radiotherapy. Its availability in the UK is currently limited to a single low-energy fixed beamline for the treatment of ocular tumours, but a number of facilities designed to treat deep-seated tumours are in development. This thesis focusses on the quantitative use of x-ray computed tomography (CT) images in planning proton radiotherapy treatments. It arrives at several recommendations that can be used to inform clinical protocols for the acquisition of planning scans, and their subsequent use in treatment planning systems. The primary tool developed is a software CT scanner, which simulates images of an anthropomorphic virtual phantom, informed by measurements taken on a clinical scanner. The software is used to investigate the accuracy of the stoichiometric method for calibrating CT image pixel values to proton stopping power, with particular attention paid to the impact of beam hardening and photon starvation artefacts. The strength of the method adopted is in allowing comparison between CT-estimated and exactly-calculated proton stopping powers derived from the same physical data (specified in the phantom), leading to results that are difficult to obtain otherwise. A number of variations of the stoichiometric method are examined, identifying the best-performing calibration phantom and CT tube voltage (kVp). Improvements in accuracy are observed when using a second-pass beam hardening correction algorithm. Also presented is a method for identifying the proton paths where stopping power uncertainties are likely to be greatest. Estimates of the proton range uncertainties caused by CT artefacts and calibration errors are obtained for a range of realistic clinical scenarios. The current practice of including planning margins equivalent to 3.5% of the range is found to ensure coverage in all but the very worst of cases. Results herein suggest margins could be reduced to <2% if the best-performing protocol is followed; however, an analysis specific to the CT scanner and treatment site in question should be carried out before such a change is made in the clinic.