Patients diagnosed with glioblastoma face poor prognosis, as the median survival from initial diagnosis is less than 15 months. Radiotherapy is considered to be one of the fundamentals of glioblastoma therapy and is given after maximum safe tumour resection or biopsy. Delineation of the gross tumour volume (GTV) and the clinical target volume (CTV) required for radiotherapy planning is performed on a combination of computed tomography and conventional, structural magnetic resonance (MR) imaging, which only visualize macroscopic features of the tumour. Due to the infiltrative nature of glioblastomas, the conventional CTV is typically defined as the GTV with an expansion of 1.5 cm. In this project, the aim was to introduce advanced MR imaging in order to visualize microscopic tumour infiltration and construct a personalized approach for CTV delineation to integrate the information provided by the advanced MR imaging. With this biological CTV, the 1.5 cm margin could be omitted and potentially lead to reduced radiation toxicity or improved local tumour control. The advanced MR biomarkers APT, VSI and rCBV correlate to cell proliferation, vasodilatation and microvascular density, respectively. Brain maps of these biomarkers from four treated glioblastoma patients were introduced in MIM Maestro®, the software package used at the Department of Radiotherapy of the Erasmus MC Cancer Institute for target delineation. In addition, imaging used for radiotherapy, the corresponding delineations, i.e. GTV, CTV and organs at risk, and follow-up imaging that showed first progression according to the response assessment in neuro-oncology criteria were uploaded to MIM Maestro®. To generate a biological CTV, a semi-automatic workflow was created that incorporates a region growing algorithm to delineate high-risk regions on the biomarker maps. Comparison of biological CTVs with the conventional CTVs showed a major reduction (ranging from 56.7% to 87.6%) in target size. Pattern of failure analysis revealed adequate coverage of the recurrence volume by the biological CTV. In three of the four patients, the biological CTV covered more than 95% of the recurrence volume. In the other patient, the coverage by the biological CTV was poor. This was partially due to the large spread of the recurrence volume. In this master’s thesis, a semi-automatic workflow is presented to take an initial step towards personalized radiotherapy for patients with glioblastoma. The introduction of advanced MR techniques was shown highly promising; future research should focus on optimization of the biological CTV generation and validation of the biomarkers in a larger cohort.

Purpose Deep inspiration breath hold (DIBH) in photon therapy as well as proton therapy (in free breathing) has been suggested to reduce cardiopulmonary and integral dose without compromising target coverage. The goal is to investigate the dosimetric impact on proton treatment plans of set-up variation and daily anatomy visualized on CBCT prior to treatment in patient with left-sided breast cancer patients with an indication for locoregional irradiation. Method For 10 patients, proton plans (4.05 Gy in 15 fractions) were made in Erasmus iCycle with a robustness setting of 5 mm and 3% range uncertainties. The CTV included the left breast (n=5) or chestwall (n=5), axillary lymphnodes levels 1-4 and internal mammary chain (IMC). The daily estimated dose was calculated on five CBCT for proton plans of 10 patients treated for left-sided breast cancer with image guided radiotherapy and surface guidance to facilitate DIBH. A workflow in MIM was created to generate virtual CTs by deforming the pCT into the CBCT. Dosimetric parameters were evaluated for four separate CTVs; CTV Breast/Chestwall, axillary lymph node levels L1+L2, L3+L4 and left IMC and included the volume, D98, V95 and V107. For OAR this included the volume, Dmean, D2cc and V5Gy for the heart and V5gy and V20Gy for the left lung. To determine whether there was a significant difference between the DVH parameters and volume between the pCT and the mean estimated dose of five fractions a wilxocon signed rank test or two tailed t-test was used. In addition, contour deformation was validated with the Dice similarity score and mean distance to agreement, and it was tested whether there was a significant difference in DVH parameters for CTV chest wall/Breast, CTV L1-L2, and heart between contours derived by the method and contours manually corrected by an experienced breast radiation oncologist on the CBCT. Results The mean and standard deviation (std) values observed in this study for the DSC and MDA are 0.98 (0.1) and 0.30 (0.2), respectively, which is in agreement with the proposed tolerances for both evaluation tools. Moreover, no significant difference was found in volume and DVH parameters between the semi-automatic contours derived from the method and the manually corrected contours. A significant difference in volume with a small absolute volume for CTV breast, Chestwall and L1-L2 was observerd and no significant difference in any of the DVH parameters for CTV breast, chestwall, L1-L2, L3-L4 and IMC. The cardiac dose did not have a significant difference in DVH parameters, but the left lung had a significant increase in V5Gy[cc] and V20Gy [cc]. Conclusion Proton treatment plans created in Erasmus-iCycle on planning CT in DIBH for patients with left-sided breast cancer with indication for irradiation of the breast/chestwall, axillary lymph nodes and IMC achieve good coverage in the mean estimated delivered dose of five fractions treated with image guided radiotherapy and surface guidance for DIBH.

Each year, more than 800 women in the Netherlands are diagnosed with cervical cancer, of which approximately half have locally advanced disease. The standard treatment for locally advanced cervical cancer (LACC) is external beam radiotherapy (EBRT) with concurrent chemotherapy followed by brachytherapy. Many patients experience some degree of treatment-related toxicity, mainly concerning the bowel, urinary tract, or vagina. Another important morbidity is hematologic toxicity (HT) due to bone marrow suppression, which might negatively impact the efficacy of adjuvant therapies. Treatment-related morbidity has a profound impact on patients’ quality of life. Proton therapy allows easier sparing of organs at risk (OARs), which might result in a decrease of treatment-related morbidities. One initiative to reduce treatment morbidities for LACC-patients was proposed in a collaborative project between Erasmus Medical Center (Erasmus MC), Leiden University Medical Center (LUMC), and Holland Proton Therapy Center (HollandPTC): the PROTECT-project. A clinical pilot study will be conducted to determine differences in dose to OARs and in morbidity outcomes when comparing state-of-the-art photon therapy with adaptive intensity-modulated proton therapy (aIMPT) for patients with LACC. Additionally, bone marrow sparing capabilities of both delivery techniques will be evaluated. The focus of this thesis is on the clinical implementation of aIMPT to facilitate the pilot-study and consists of three parts. The thesis started with a systematic review of the literature about the relationship between bone marrow dose and HT in LACC-patients treated with primary chemoradiation. The review has been submitted for publication. There was a scarcity of studies investigating the relationship between bone marrow dose and HT and clinically useful prediction models were not available yet. The majority of the studies defining bone marrow as the whole pelvic bone found a significant association between bone marrow and HT, in contrast to studies evaluating lower density marrow spaces or active bone marrow. Future studies may use whole pelvic bone contouring to develop normal tissue complication probability models. Secondly, the development and implementation of the treatment planning strategy for LACC-patients in HollandPTC were proposed. Uncertainties arising from proton therapy delivery were identified and strategies to address these uncertainties were determined. The proposed aIMPT-strategy for LACC-treatment consisted of a plan-of-the-day-approach with margins and robust planning. Further work includes establishing the balance between robustness settings and margins and optimizing the clinical implementation of the plan-of-the-day-strategy. Lastly, the workflow for LACC-patients in Erasmus MC was translated into the HollandPTC environment. Requirements for the new workflow were generated with input from both the investigator and a risk evaluation with the users. A workflow was designed and translated into HollandPTC's situation. Secondly, the implementation of the plan-of-the-day-strategy in the treatment management process of the oncology information system ARIA was investigated. Recommendations were made to finalize and validate the implementation of the workflows. This thesis provides a base for the clinical implementation of aIMPT for LACC in HollandPTC. The systematic review gives guidance for bone marrow sparing techniques in Erasmus MC and HollandPTC. Additionally, a combination of a plan-of-the-day-approach with margins and robust planning was identified as the most optimal treatment planning strategy. Lastly, an implementation strategy for the clinical workflow and treatment management process in HollandPTC was determined. Further work should focus on finalizing and validating the clinical implementation to facilitate PROTECT's clinical pilot study in HollandPTC.

AimTreatment with Proton Beam Therapy (PBT) is highly complex due to a variety of activities integrated into the workflow to ensure treatment quality and patient safety. The effects of changes to the workflow with the intend to scale up a PBT facility are therefore hard to predict. The purpose of this study was to develop a forecasting simulation-based application which could predict the effects of systematic optimisation of the healthcare processes within a PBT facility. Methods A Discrete Event Simulation application was developed which modelled the entire workflow of a PBT facility. The simulation was validated using real-world historical data. Scenarios were simulated according to a waterfall approach to predict potential capacity bottlenecks. A list of recommended modifications to the current processes was developed which can be used as guidelines towards a systemic increase in capacity. Results The first simulated scenario extrapolated the patient distribution of 2020 to match a target of 600 patients treated. A total number of 475.8±12.67 patients were simulated to be treated. The capacity bottlenecks were caused by retention of the planning resources. The second scenario simulated 556.3±11.97 treated patients. The capacity bottlenecks were caused by too little availability of radiation oncologists. The third scenario simulated 588.3±4.26 patients. The capacity bottlenecks were caused by too little availability of the gantries. The fourth scenario simulated the target: 601.4±7.72 patients. Conclusion In this project, we employed a validated DES simulation to model the in-house workflow of HollandPTC and to make predictions on capacity, throughput, patient flow, and availability of resources. The developed simulation is expected to be applicable to other PBT facilities around the world. The extent to which the simulation is applicable should be further explored.