With FLASH proton radiotherapy, healthy tissue is spared more compared to conventional proton therapy. The FLASH effect is present at high fractional doses of more than 8 Gy, at ultra-high mean dose rates of more than 40 Gy per second and at dose delivery times of less than 200 milliseconds. However, particle accelerator intrinsic uncertainties can influence the FLASH effect negatively. FLASH proton therapy is affected by pencil beam positioning errors and by proton beam current fluctuations. In this work, these two types of uncertainties were added to a Gaussian two-dimensional analytical dose model. The impact of pencil beam placement errors was evaluated on dose deposition and related to clinically used metrics. These are the V95, V107, D2 and D98. The constraint on the V95 was violated for 5\% of patients first. For all evaluated FLASH dose fields, the allowed Gaussian pencil beam placement error is less than 1.0-mm in standard deviation. A trade-off between target coverage and the level of FLASH effect was found. Proton beam current fluctuations were coupled to the pencil beam scanning dose rate (PBSDR98), the minimum dose rate for 98\% of the target volume. For all evaluated FLASH fields the permitted beam current fluctuation was 6.8\%. This is considered more achievable than the limit on pencil beam placement errors. Proton FLASH radiotherapy is feasible, but proton beam characterisation is required to quantify for which patients this is the case.

The PBSDR is sensitive to added uncertainties and contradicts our current understanding of the FLASH effect. In this thesis, a more robust metric is developed which depends on the radiolytic oxygen depletion hypothesis for the FLASH effect. This metric is called the FER_eff. The oxygen concentration over time in a cell is modelled with an ordinary differential equation (ODE) involving an oxygen depletion and re-oxygenation term. The FER_eff can be calculated with the oxygen concentration over time for a treatment plan. Currently, The onset of the FLASH effect lies between a prescribed dose of 8 Gy and 16 Gy. This is in line with the FLASH dose threshold. The shortcomings of the PBSDR are dealt with.

A three-dimensional uncertainty analysis can be done with a semi-analytical dose engine from the TUD. With this engine, changes in dose deposition are coupled to Hounsfield unit (HU) perturbations without the necessity of a full dose re-computation. To study the machine uncertainties, an EMC FLASH treatment plan formed with iCycle was recreated with the TUD dose engine. The iCycle optimisation results contain all the required information for a dose calculation. The gamma pass rates between the iCycle dose and engine dose were satisfactory for the target but not good enough for an organ-at-risk (OAR) yet. Similarity can be improved by adjusting the dose recreation procedure. When the iCycle dose and engine dose are comparable, a trustworthy clinical uncertainty analysis can be done. The idea is to simulate field and individual pencil beam placement errors by shifting the original patient CT to a virtual CT. First, it should be studied if the computed dose response is valid for a combination of CT shifts and HU perturbations. In a later stage, pencil beam placement errors should be coupled to the clinically used ICRU metrics and constraints. The impact of beam current fluctuations can also be studied in the future.

During pre-clinical research on proton therapy, validating the dosimetry is important for accurate and representable results. To ensure that research outcomes can eventually be implemented in clinical practices, it is equally as important to also take biological effects into account. The aim of this thesis was, therefore, to dosimetrically and biologically commission a pre-clinical proton therapy research line. A phantom was designed, 3D-printed and irradiated to check accurate positioning in the beamline. Radiochromic film was used as a dosimeter at different positions within the phantom. The blackening of this radiochromic film after proton irradiations was quantified to obtain information on the dosimetry. It seemed that the phantom was correctly positioned at different places in the spread-out Bragg peak. However, accurate and precise dosimetry appeared to be difficult with radiochromic film. The added compensator successfully gave more uniform profiles throughout the whole depth of the phantom. Furthermore, the dose response of spheroids made from FaDu tumour cells was characterised and
compared to the dose response of cells grown as a monolayer. Spheroid growth and viability, based on the cellular ATP levels, were used as biological endpoints. A different dose response of FaDu spheroids was found when compared to that of cells, however, no clear explanation was found and more research remains to be done. Overall, with some further research, this 3D-printed phantom, along with the tumour spheroids, can
be implemented to validate a pre-clinical proton therapy research line.

Background: Histopathological examination in the diagnostic workflow of oropharyngeal squamous cell carcinoma (OPSCC) is essential. We aimed to develop a machine learning pipeline to predict human papillomavirus (HPV) status in OPSCC patients based on clinical variables and multiparametric magnetic resonance imaging (MRI).
Methods: In a dataset of OPSCC patients (n=59), we extracted features from three categories: clinical variables; histogram parameters from diffusion weighted imaging (DWI)-MRI model; radiomics based on T2-weighted and DWI-MRI. We performed ten-times repeated stratified five-fold cross-validation and divided each outer training set (80%) into an inner training set (80% of outer training set) and validation set (20% of outer training set) using five-fold stratified cross-validation. We performed three types of feature selection methods (LASSO, statistical analysis and manual selection), tuned and trained seven classifiers (logistic regression, k-nearest-neighbours, naive bayes, random forest, support vector machine, XGBoost and LightGBM) to find the optimal combination of features, hyperparameters and classifier on each inner training set. We ensembled the inner fold models to fit on the outer training set and tested on the outer test set (20%). We constructed additional models with subsets of the features.
Results: the combined model area under the curve was 0.793±0.136. Models including clinical features outperformed models without clinical features (p<0.001). Features from all feature categories were selected for the combined model.
Conclusion: we were able to predict HPV status in OPSCC patients using multiparametric MRI and clinical variables with reasonable accuracy, though retraining and validating on larger, external datasets is needed before implementation in clinic.

The goal of radiotherapy is to maximize the dose to the target while minimizing the dose to normal tissue. Treatment plans are optimized for this goal and dose delivery is improved in accuracy and precision. The optimization is based on the delineations of the volumes of interest on the medical images of the patient. The problem is that these delineations contain uncertainties and the effect of these uncertainties become more pronounced as the accuracy and precision of dose delivery improves. The delineation uncertainties are caused by various factors such as knowledge and experience of the observers, guidelines, and image quality and modality. The goal of this thesis is to research the effects of delineation uncertainties. Uncertainties are characterized using a rolling ball algorithm (RBA) to modify the delineation. The radius of the ball represents the uncertainty and ranges from -5 mm to 5 mm for the clinical target volume (CTV) and -2 mm to 2 mm for the brain stem. The effect of these uncertainties will be researched for both fixed and re-optimized dose distributions. These are then used as input to create a model that will simulate the dose distributions for different uncertainties using Polynomial Chaos Expansion (PCE). PCE will be used to model dose volume histograms (DVH) of the CTV and the brain stem. The dosimetric effect will be determined by setting confidence intervals in D98% of the CTV and D2% of the brain stem. The widths of the confidence intervals in these two metrics represent the dose uncertainty. This thesis uses three sets of patient data. Each patient had a CTV close to the brain stem. Dose uncertainty in the two metrics was found to increase as the uncertainty of CTV and brain stem delineation increases. For a fixed dose distribution, a delineation uncertainty of 0.75 mm to 1.25 mm in the CTV would lead to a dose uncertainty of 2 Gy in the D98% of the CTV. A delineation uncertainty of 0.25 mm to 0.5 mm in the brain stem would lead to the same dose uncertainty in D2% of the brain stem. For a re-optimized dose distribution, a combined delineation uncertainty of 1.25 mm for two patients and 4.5 mm for one patient would lead to a dose uncertainty of 2 Gy in D98% of the CTV. For the same dose uncertainty in the D2% of the brain stem, there would be a combined delineation uncertainty between 1.0 mm and 4.5 mm. For all three patients, the dose uncertainty in the D2% was more sensitive to delineation uncertainties in the brain stem. The effects of these uncertainties will depend on the nominal situation. For all patients a 2 Gy dose uncertainty corresponds to 2.85% of the prescribed dose to the CTV and 3.33% of the maximum dose constraint of the brain stem. One patient was on the boundary of underdosing the CTV in the nominal situation and a 2 Gy uncertainty would be sufficient to underdose the CTV. The nominal D2% for all three patients was sufficiently low that it is unlikely it would exceed the maximum dose constraint.

With almost 900.000 new patients per year suffering from head and neck squamous cell carcinomas (HNSCC), who after radiotherapy treatments experience severe side effects, the focus is drawn to proton therapy. Proton therapy results to less side effects since healthy tissues surrounding the tumour receive less radiation dose. This results from the proton’s specific depth-dose profile with its Bragg peak.
To further reduce the effect on surrounding tissues, major improvements should be made in understanding the biologic response to proton therapy which will eventually lead to enlarging the therapeutic window. Here in vitro analysis with DNA damage repair inhibition or increasing proton dose rates can be performed to assess which DNA repair pathways repair radiation induced DNA damage and to assess the effect of proton dose rates on biological tissues. This will be investigated in vitro, while in vivo experiments are necessary as well. However, currently most mice are irradiated with protons in the plateau of the Bragg curve instead of the Bragg peak. Therefore, a dosimetric pipeline should be designed to allow for accurate placement of mouse tumours in the proton’s Bragg peak.
In this thesis, the osteosarcoma- and HNSCC-derived U2OS and FaDu cell lines were incubated with non-homologous end-joining or homologous recombination inhibitors during x-ray and proton irradiations. We have shown a radiosensitising effect of the non-homologous end joining inhibitor AZD7648 on FaDu cells during x-ray irradiation, but an effect during proton irradiation could not be proved nor neglected. The homologous recombination inhibitor B02 could not effectively inhibit homologous recombination and was shown to not affect clonogenic survival of FaDu during X-ray irradiations. The observed radiosensitising effect of the non-homologous recombination inhibitor AZD7648 can be exploited in patient selection based on already existing DNA damage repair deficiencies in the tumour. Furthermore, combination therapies could be used of photon irradiations with AZD7648 targeted to the tumour to artificially enlarge the therapeutic window.
Besides this, the HNSCC-derived FaDu cells were irradiated with varying dose rates to assess induction of a FLASH effect. This FLASH effect is usually observed after irradiations of >40 Gy/s resulting in a reduction of normal tissue complications while tumour control is maintained. In our analysis, small differences in low dose rates did not have any impact. The experimental set up for proton FLASH irradiations of cells was prepared and though we performed the first set of experiments no definite conclusion could be drawn due to the level of biological variation we observed.
Of course, differential effects between tumours and tissues like the FLASH effect should be investigated in vivo. Therefore, a set-up should be created to irradiate the mural tumour with Bragg peak protons. To reach this, two micro-CT scanners were calibrated to link Hounsfield units to stopping power ratios. The proton range in mice was determined and a 3D-printed mouse-like phantom was irradiated. In this thesis, determined stopping powers of all CIRS phantom inserts except for lung tissues were accurate with a maximum deviation of 2% or 6.5% after calibration with QuantumGx or VECTor micro-CT scanners. Larger deviations were observed for CIRS lung inserts or Gammex inserts. The irradiated gafchromic films inserted in the murinemorphic phantom showed dose distributions visualising the mouse’s anatomy, yet the dose was too low due to irradiation in the distal edge of the Bragg peak. The latter was confirmed with Monte Carlo simulations. This dosimetric set-up to place mice tumours in the proton Bragg peak should thus be slightly improved and can then be of great value for in vivo experiments of proton therapy. This enables execution of many new experiments with DNA damage repair inhibition and FLASH irradiations, potentially leading to an increase of the therapeutic window in proton therapy and less side effects for HNSCC-patients.

The delineation of the regions of interest (ROIs) plays an important role in the radiotherapy workflow. The ROIs include the gross tumor volume (GTV), the clinical target volume (CTV), the planning target volume (PTV) and organs at risk (OARs). There are however uncertainties related to the delineation of the ROIs due to inter­observer variability between radiation oncologists caused by e.g., a lack of consensus on anatomic definition or a lack of contrast in medical images. The largest inter­observer variability has been found in esophageal cancers, head and neck cancers, and lung cancers. To pre­ vent inter­observer variability, auto­contouring software can be used to delineate the ROIs. There are however also uncertainties in the delineations made by auto­contouring software. The purpose of this study was to perform an accurate evaluation of the dosimetric effect of delineation uncertainties. To do so, first a method to characterize the delineation uncertainties had to be found. The delineations uncertainties were characterized with principal component analysis (PCA). By performing PCA on a set of delineations, the eigenmodes which represent the variations between the delineations can be found and new random delineations based on the eigenmodes can be formed. To determine the dosimetric impact of the delineation uncertainties, two cases were investigated: (1) the dosimetric impact of delineation uncertainties for a fixed dose distribution; and (2) the dosimetric impact of delin­ eation uncertainties for a dose distribution reoptimized for every possible realization of a delineation. For the fixed dose distribution, Polynomial Chaos Expansion (PCE) was used as a meta­model for the dose volume histogram (DVH) of the target, and for the reoptimized dose distribution PCE served as a meta­model for the total dose distribution and the DVHs of the target and other ROIs. The delineation uncertainties of two data sets were analyzed: (1) 12 manual delineations of the GTV of a hepatocellular carcinoma patient; and (2) 90 auto­contours of the CTV and brainstem of a head and neck patient. The variation of the manual delineations of the GTV could be accurately described by 5 eigenmodes, while 45 eigenmodes were needed to describe the variations of the brainstem auto­ contours. The delineation uncertainties in the auto­contours of the CTV could not be characterized by PCA due to the shape of the CTV. The dosimetric effect of the delineation uncertainties of the manual delineations for a fixed dose distri­ bution was investigated for both an intensity modulated proton therapy (IMPT) plan and a volumetric­ modulated arc therapy (VMAT) plan for 10,000 random delineations of the CTV. For this patient the CTV was equal to the GTV. In the VMAT plan, the CTV received sufficient dose for all delineations, but the PTV was underdosed in 17.1% of the delineations. In the IMPT plan, the CTV was underdosed in 69.0% of the delineations. This percentage of underdosed CTV delineations in the IMPT plan was reduced when the plan was made robustly. The results for the fixed IMPT dose distribution should however be verified with a more accurate PCE model. A proof of principle for the PCE as a meta­model for the reoptimized dose distribution and DVHs of the target and other ROIs was shown. However, a more accurate PCE model with a higher polynomial order would be needed to analyze the effects of the reoptimization on the dose delivered to the ROIs. It has been shown that the dosimetric impact of delineation uncertainties can be modelled using PCE. This is a first step towards systematically and quantitatively taking into account delineation uncertainties in radiotherapy treatment planning. In future research the analysis of the dosimetric impact of the un­ certainties can e.g., be used in adaptive radiotherapy in which auto­contouring is used. By knowing the dosimetric impact of the uncertainty, treatment plans could be optimized such that a structure receives its target dose with a certain probability or critical areas where the dosimetric impact of the delineation uncertainties is large could be flagged such that these areas are checked before treatment.

FLASH proton therapy is a growing field of research, especially due to its biological benefits in radiation oncology: sparing healthy tissue while delivering the treatment within a millisecond. However, instead of sparing healthy tissue, the conventional FLASH approach, using transmission beams, damages the tissue behind the distal edge of a tumour. Therefore, this approach is less attractive in some clinical applications of FLASH proton therapy. To solve this problem, the use of a ridge filter and patient-specific range compensator, to shift the spread-out Bragg peak (SOBP) of the proton beam to the tumour, is proposed. In this research, the clinical feasibility and acceptability of FLASH-compatible treatment plans, optimized with multiple, Monte Carlo-simulated ridge filter beams, is analysed. An SOBP-database is generated using energy spectrum approximations and interpolations of energy spectra retrieved from Monte Carlo simulations in TOPAS. To obtain optimized FLASH-compatible treatment plans for neuro-oncological targets, this database is implemented in the in-house treatment planning software of the Erasmus Medical Center, iCycle.  The resulting treatment plans show that it is possible to generate FLASH-compatible treatment plans using a ridge filter. A FLASH enhancement ratio between 1.4 and 2.1 would potentially give clinically acceptable plans for the three patients considered. In some optimized plans, the homogeneity of the tumour dose is also increased. A limitation of this research is that configuration of a stable ridge filter beam treatment plan optimizer appears to be challenging. Besides this, the FLASH enhancement ratio and the dose rate are not taken into account to find the regions in the patient where the FLASH conditions (dose > 8 Gy, dose rate > 40 Gy/s and treatment time < 0.1 s) are met.  Recommendations for future research include: implementing the FLASH enhancement ratio and the dose rate optimization in treatment plan optimization; investigating the influence of fractionation ofa FLASH treatment plan on the tumour control and the healthy tissue irradiated; study the relative biological effectiveness (RBE) and the biological character of FLASH radiotherapy, and investigate the clinical potential of a combination of FLASH and non-FLASH treatment.

Radiotherapy (RT) is an important modality in treatment against cancer. Developments in this modality are necessary for improvement of patient complications and survival. Aside from fractionation and precise irradiation, FLASH radiotherapy could be a third way to significantly increase the therapeutic window of radiotherapy.The FLASH effect is a biological, healthy tissue sparing effect that is found in tissue that receive a high dose (>10 Gy) within a very-short irradiation time (<100 ms). Although the mechanics behind the FLASH effect remain unknown, it is found to benefit a large variety of tissues and organs. Nevertheless, FLASH-RT still lacks clinical translation and implementation of FLASH irradiation is limited by current technology. However, the extremely high dose rates required for FLASH can readily be achieved using cyclotron accelerated proton transmission beams. Cancer patients with small lung tumours are a preferred starting point for clinical translation of FLASH because (i) transmission beams are of special benefit for lung tumours since they mitigate for range uncertainties and contain a sharp lateral penumbra, (ii) high doses are required for the FLASH effect to occur and hypofractionation is not uncommon for lung patients, and (iii) the very short irradiation times and high doses in combination with gating allow smaller treatment margins for moving tumours.In this study, we took a first step towards intensity modulated proton therapy (IMPT) with FLASH treatment plan optimisation by (i) investigating the most delivery-time effective way to irradiate a field, (ii) proposing an optimisation method to maximise FLASH within a treatment plan, and (iii)analysing and evaluating FLASH treatment plans. Because increased pencil-beam (spot) separation showed to benefit the pencil-beam scanning(PBS) delivery time of a field, spot overlap minimisation was proposed as optimisation method for FLASH. Treatment plans using 3, 5 and 7 transmission beams were generated with and without FLASH optimisation for 6 small lung tumour patients. Although spot overlap minimisation doesoccasionally improve delivery time for a limited number of beam angles, the overall treatment plan does not benefit from the optimisation. Therefore, spot overlap minimisation cannot be used for FLASH optimisation in clinical IMPT treatment planning. Recommendations for future research include optimisation on PBS delivery time and PBS pattern optimisation.

Proton radiotherapy has a dosimetric advantage over photon therapy to spare healthy tissue closely positioned to the tumor mainly due to the absent exit dose. In The Netherlands, the Proton therapy centers currently take a relative biological effectiveness (RBE) of 1.1 compared to photons to deliver an iso-effective treatment. However, initial clinical evidence indicates a variable proton RBE in brain patients with the linear energy transfer (LET) as an important physical parameter. The LET significantly increases at the end of the radiation field, and contributes to an increased probability to develop brain lesions. With the introduction of radiation response models, the first goal of this thesis is to evaluate the impact of the RBE/LET effect in intensity-modulated proton therapy (IMPT) plans. Furthermore, the main goal is to reduce the RBE/LET effect in treatment planning.

We incorporated the probability of lesions origin (POLO) model published in literature to determine the RBE model-based normal tissue complication probability (NTCP) for three glioma patients treated with IMPT at HollandPTC, The Netherlands. The dose and LET distributions were computed using a Monte Carlo system. For the investigation of the RBE/LET effect in treatment planning, we modified several beam settings of the clinical IMPT plan, including the beam angle, beam energy, and robustness. Furthermore, we combined treatment modalities to reduce the NTCP.

We compared the results of the clinically used IMPT plan with the results obtained by the modified IMPT plans. The local redistribution of LETd leads to a decrease in NTCP up to the point when the LETd becomes uniform. The robustness did not reveal deviations in terms of the NTCP. By choosing appropriate beam angles that result in a smeared out
LETd distribution, the NTCP does not improve for small deep located tumors, improves relatively modest by 11.6% for elongated tumors, and significantly improves by 37.0% for large, superficially located tumors. The inclusion of partial transmission beams lowers the NTCP by 30-50% relative to the clinical IMPT plan while limiting the relative increase in mean brain dose by 5-16%. When comparing the IMPT plan with the photon plan used for plan comparison, the VMAT plan always results in the lowest NTCP and provides a relative improvement in NTCP by 60-75%. Meanwhile, the mean brain dose significantly increases by 50-80% compared to the clinical IMPT plan. Intermediate NTCP-Dmean(brain minus CTV) values are achieved when combining protons with the photons or by including proton transmission beams.

In general, we can conclude that the inclusion of partial proton transmission beams is more promising than choosing appropriate beam angles to lower the RBE/LETd effect. However, further optimization of transmission beams is required. Moreover, an improvement in NTCP is always at the cost of the mean dose to healthy tissue. On top, our results support further investigation to combine different modalities, like protons and photon fractionation.