To reduce the probability of complications in proton therapy, while maintaining a high tumor control probability, adaptive treatment can be applied. In adaptive treatments, the treatment plans are frequently assessed and adjusted to, for example, account for anatomical changes. Ideally, daily adaptive treatment would be implemented, where every day a repeat scan is made and the treatment plan is adjusted. However, due to computational limitations, daily adaptive treatment is not possible yet. Quality assurance (QA) is a vital part of the proton therapy workflow. Intending to implement daily adaptive treatment, fast-working quality assurance tools are necessary. The goal of this thesis is to calibrate and adapt a deterministic proton transport algorithm to reconstruct the delivered dose using log files, which can be compared to the planned dose as a QA tool.

To achieve this, Yet anOther Dose Algorithm (YODA) was calibrated to the popular planning software RayStation, by optimizing the input parameters of YODA to minimize the difference in dose between YODA and RayStation for a 0° gantry angle single spot in a homogeneous water phantom. From this calibration, beam data library (BDL) files were created for cases without a range shifter and with range shifters of thicknesses 2 cm, 3 cm and 5 cm and planned spot energies ranging from 70 MeV to 190 MeV. An approximation to improve the inclusion of the effect of nuclear interactions was added to YODA. The lowest passing rate found was 99.47% for a 190 MeV spot without a range shifter, therefore the calibration was successful. The passing rate decreased for high energies, likely due to the crude approximation to deal with nuclear interactions. Other ways to include
the effect of nuclear interaction should be investigated to further improve the calibration results. After the calibration was complete, three experiments were performed.

First, simple treatment plan comparisons were performed using the BDL files and a homogeneous water phantom, including plans containing a single spot irradiated from gantry angles ranging from 10° to 90°. To account for the angled beams, a beam splitting algorithm was used. It was observed that the BDL files are specific for the isocenter to CT volume surface distance, as the boundary conditions of YODA are at the CT volume surface while the treatment plans define spots at the isocenter in air. To include this effect, the BDLs should contain beamlet parameters at the isocenter, from which the beamlet parameters at the CT volume surface can be calculated. The calibration procedure for the spatial spread, angular spread and correlation needs to be adjusted. Alternatives to the beam splitting algorithm should be investigated, as this algorithm inadequately reflects reality when a beam enters the CT volume under an angle.

Second, YODA assumes that spots are laterally symmetrical, however, in reality, spots are ellipse-shaped. To solve this, the asymmetrical spot solution to the Fermi-Eyges equation was derived. The difference in integrated Fermi-Eyges flux between the symmetrical and asymmetrical spot was calculated for realistic combinations of lateral spread, angular spread and correlation. The mean error in integrated Fermi-Eyges flux, relative to the maximum, induced by assuming lateral spot symmetry, around the central beam axis is significant, as it ranges from 0.6853% to 3.071% at the entrance of the CT volume and from 0.4710% to 4.957% at the Bragg peak. Therefore the asymmetrical spot solution should be implemented, after which, YODA should be re-calibrated

Third, the error induced by systematic errors in the log file was investigated. The plan contains a target cube centered in the homogeneous water phantom irradiated by a 0° gantry angle beam. By perturbing each energy layer randomly using a uniform distribution, where the maximum perturbation was 0.8 mm in spot position, 1% for MU and 0.1% for energy, the magnitude of the dose difference was calculated. The mean differences in dose in the target cube induced by randomly perturbing each energy layer were 0.1204% ± 0.0408% in x, 0.1700% ± 0.0324% in z, 0.2592% ± 0.1595% in MU and 0.4802% ± 0.1558% in energy. These differences are small compared to the error induced by assuming symmetrical spots, note that the differences in spatial spread were an order of magnitude bigger than the perturbation in spot position. Before this investigation on the effect of systematic errors can continue, the asymmetrical spot solution needs to be implemented and the problems discovered with angled beams should be solved.

The calibration was successful, and additional extensions and alterations have been identified to further improve YODA before it can be used as the described patient-specific quality assurance tool.

Dose calculations in proton therapy need to be computed as fast as possible for successful cancer treatment planning and execution. The dose calculation algorithms that provide enough accuracy for treatment planning, takes too much time to utilise; therefore there is a need for faster alternatives. One of the alternatives is using a deterministic semi-analytic numerical algorithm for EM interactions. This alternative in its current state is not accurate enough, and therefore it is sought to include the effects of secondary protons on the total dose distribution of the deterministic semi-analytic numerical algorithm, using convolutional methods. In this thesis an attempt is made to find a kernel that, when convoluted with a primary proton flux, produces the desired secondary proton dose. The parameters of two different types of kernels, the Gaussian kernel and Fractional Filter kernel, are optimised and their resulting shapes are presented. Furthermore, the secondary proton dose through the convolution of the primary proton flux and the different kernels are presented. The doses obtained from the optimal kernels are compared with the target dose on the shape and a measure of quality: the gamma index passing rate. Found was that the Fractional Filter kernel can produce both asymmetric doses and symmetric doses, while the Gaussian kernel can only produce symmetric doses. The passing rate was found to be 29.41% for the Fractional Filter kernel and 17.65% for the Gaussian kernel. Thus, the Fractional Filter is better for estimating secondary proton dose distribution through convolutional methods than using a Gaussian kernel. but insufficient due to the low passing rate. A suggestion for improvement is applying skew-Gaussians in the Fractional Filter kernel or by applying other asymmetric kernels.

In order to create radiotherapy treatment plans for cancer patients, dose calculations need to be done as quickly as possible to get accurate results. However, current dose calculation algorithms take too much time to be deployed effectively. The current in house algorithm of the Medical Physics and Technology Section at the TU Delft, attempts to solve this problem by utilising a deterministic algorithm that has a significant time advantage over Monte Carlo algorithms. However, this comes with the cost of inaccuracy, one of which is that it assumes
all dose is deposited locally along the beam path. This is inaccurate as secondary particles created from non-elastic nuclear interactions can deposit their dose far from the beam path due to retaining significant kinetic energy. This thesis attempts to reduce this inaccuracy by mapping and quantifying the secondary particles to assess their contribution in non-local dose deposition. And analysing the relevant particle’s energy and angle distributions to gain insight into the development of the particle's characteristics with depth. Thereafter the relevant
particle’s are then utilised as a source to emulate their production in a primary proton beam at different depths to obtain the relevant 3D dose distributions. The analysis concluded that secondary protons are the most relevant secondary particle as they contribute to 88% of the secondary dose and have a significant range to deposit their dose non locally. By utilising the secondary protons as a source, it was found that the relative error between the integrated depth dose (IDD) of the scored protons and the IDD obtained directly from Monte Carlo simulations is equal to 5.1% in the z-direction and 3.4% in the x and y-direction. The absolute difference was found to be 1.54 × 10−5 Gy which is equal to 0.096% of the total dose and 2.75% of the dose contributed by all secondary particles. The results show that the methodology can produce accurate 3D dose matrices for secondary protons at different depths, which can then be used to improve the accuracy of the in house algorithm by adding the precalculated 3D dose matrices to the algorithm

Cancer is a disease that causes almost 10 million deaths each year. Currently, there is no perfect treatment for it. However, there is a promising treatment called proton radiotherapy. This works almost the same as one of the older cancer treatments called photon radiotherapy. However, radiotherapy with protons has an advantage in comparison with radiotherapy with photons. This advantage lies in the way the protons lose their energy when going through tissue. The protons deliver most of their dose in a very small region. Cause of this advantage, proton radiotherapy can deliver a lot of dose into the tumour while minimizing the dose delivered into healthy tissue. But this advantage can change into a disadvantage when the location of the tumour moves a few millimeters.
Therefore ideally a scan is taken each time the patient comes in, so the location of the tumour is known very accurately. After the scan it is best to immediately create a treatment plan and do the treatment session. But creating a treatment plan takes to much time to be able to do that. Mainly, this is because the calculation of the dose distribution is not fast enough. This report studies a faster method for the calculation of the dose distribution. The method is derived by the Medical Physics \& Technology group from TU Delft. This method is currently not accurate enough to use for treatment planning. The problem of the method is that the dose due to nuclear interactions is not included correctly. The goal of this report is to make the method more accurate by adding the nuclear dose caused by secondary particles formed due to inelastic nuclear interactions to the dose calculated by the existing method.
The nuclear dose is calculated using a convolution of a kernel with the proton flux. The nuclear dose of the following secondary particles is calculated: alpha particles, deuteron particles and secondary protons. Adding the nuclear dose caused by these three secondary particles increased the accuracy of the model by 0.36 percent. However adding the nuclear dose calculation increased the time needed to calculate the dose distribution with 18625 percent. By calculating the convolution using the fast Fourier transform this could be decreased by a factor of 11. However adding the nuclear dose calculation to the fast method increases the time needed to calculate the dose distribution too much. Therefore the calculation of the dose distribution is not fast enough to scan a patient and immediately start with the best possible treatment plan using the fast method with the nuclear dose calculation added.