Concerns arise in radiation therapy for head and neck cancers when dental prostheses are involved. These prostheses are high-density materials that induce image artifacts in computed tomography (CT) scans used for dose calculation. Two approaches are utilized in mitigating the impact of these artifacts on the accuracy of dose calculation. First, metal artifact reduction (MAR) algorithms or dual-energy CT scans are used to recover image quality. Second, a planning protocol is adopted whereby residual artifacts are manually contoured and assigned appropriate densities. This study evaluated the current planning process using a holistic approach. In this work, an axial section of a head phantom containing dental implants at the level of the oral cavity was constructed and scanned using various protocols on two different commercial scanners; Philips and Siemens, to assess the appearance of artifacts. An MVCT image set was merged with the corresponding kVCT image to improve visualization of the dental implants for use in density overrides. Three ion chamber measurement points in the simulated mouth facilitated the determination of measured dose which was compared to calculated dose at various single beam irradiation geometries. The influence of density override values on agreement between calculation and measurement was investigated for each geometry and imaging modality. Percent error was computed, and initial results compared to results manipulated by use of; a CT density table (Head); density overrides of walls and wax; and density overrides of walls, wax, and effective density of saturation regions. The study established that normal tissue doses are not significantly affected by metal artifact reduction (MAR) algorithms, and improvements in dose calculation compared to uncorrected CT images are small. Furthermore, the inclusion of a MVCT image set improved implant visualization reducing the treatment planning time while providing more information. Evidence led to the deduction that manual overrides of effective density for clipped OMAR CT pixels reduce dose calculation errors. When the phantom was configured with amalgam and Co-Cr-Mo alloy dental implants the effective density of these implants was found to be 4.5 g/cm3. When the phantom was configured with implants containing amalgam and gold, the effective density of amalgam in the presence of gold was 5.5 g/cm3 while gold had an effective density of 6.5 g/cm3. The median and maximum range of errors for the uncorrected images were ± 0.6 % and 7.4% respectively for the phantom configured with amalgam and Co-Cr-Mo (tray one) and ± 0.5 % and 18.1 % respectively for the phantom containing amalgam and gold (tray two). The median and maximum range of errors for the corrected images after applying overrides of effective densities were ± 0.5 % and 4.7% respectively for tray one and ± 0.3 % and 7.7 % respectively for tray two. In conclusion, introduction of density overrides of walls, wax and effective density of high-density materials can reduce the errors induced by metal artifacts and improve the accuracy of dose calculations in treatment planning systems to deliver the relevant dose to a target organ. / Thesis / Master of Science (MSc)

External radiotherapy is a common treatment technique for cancer. It has been shown that radiation therapy is a both clinically and economically effective treatment for many types of cancer, even though the equipment is expensive. The technology is in constant evolution and more and more sophisticated and complex techniques are introduced. One of the main tasks for physicists at a radiotherapy department is quality control, i.e. making sure that the treatments are delivered in accordance with the dosimetric intentions. Over dosage of radiation can lead to severe side effects, while under dosage reduces the probability for patient cure. The present thesis is mainly focused on the verification of the calculated dose. Requirements for independent dose calculation software are identified and the procedures using such software are described. In the publications included in the thesis an algorithm specially developed for verification of dose calculations is described and tested. The calculation uncertainties connected with the described algorithm are investigated and modeled. A brief analysis of the quality assurance procedures available and used in external radiotherapy is also included in the thesis. The main conclusion of the thesis is that independent verification of the dose calculations is feasible in an efficient and cost effective quality control system. The independent calculations do not only serve as a protection against accidents, but can also be the basis for comparisons of the dose calculation performance at different clinics.

This dissertation explores beta dose profile of microspheres packed in arteries, various source geometries of 142Pr that can be used for therapeutic purpose, and dose backscatter factors for selected beta sources. A novel treatment method by injecting microspheres into feeding arteries of arteriovenous malformation (AVM) is under pre-clinical investigation. To optimize radiation dose to the clinically important area, i.e. arterial wall, preliminary dosimetric studies were needed. Monte Carlo calculations were performed for several geometries simulating arteries filled with microspheres packed by random packing methods. Arterial radii used in the simulation varied from 50 mm to 3 mm; microsphere radii varied from 10 mm to 0.7 mm. Dose varied significantly as a function of microsphere size, for constant arterial sizes. For the same sizes of arteries, significant dose increase was observed because of inter-artery exposure for large arteries (> 0.1 cm rad.) filled with large microspheres (> 0.03 cm rad.). Dose increase between small arteries (0.03 cm rad.) was less significant. The dose profiles of prototype 142Pr beta brachytherapy sources were calculated using MCNP 4C Monte Carlo code as well as dose point kernel (DPK) for selected cases. Dose profiles were similar to beta sources currently used indicating that 142Pr can substitute for current sources for certain cases and the DPK was closely matched with MCNP result. Backscattering of electrons is a prominent secondary effect in beta dosimetry. The backscattering is closely correlated with factors such as geometry of source and scattering material, and composition of scattering material. The backscattering factors were calculated for selected beta sources that are currently used as well as potentially useful sources for therapeutic purpose. The factors were calculated as a function of distance from the interface between water and scatterers. These factors were fit by a simple function for future incorporation into a DPK code. Backscattering effect was significant for short distance from the surface of interface between water and scattering material.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18877号 / 医博第3988号 / 新制||医||1008(附属図書館) / 31828 / 京都大学大学院医学研究科医学専攻 / (主査)教授 武田 俊一, 教授 富樫 かおり, 教授 増永 慎一郎 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

<p>Scanned proton beams offer the possibility to take full advantage of the dose deposition properties of proton beams, i.e. the limited range and sharp peak at the end of the range, the Bragg peak. By actively scanning the proton beam, laterally by scanning magnets and longitudinally by shifting the energy, the position of the Bragg peak can be controlled in all three dimensions, thereby enabling high dose delivery to the target volume only. A typical scanned proton beam line consists of a pair of scanning magnets to perform the lateral beam scanning and possibly a range shifter and a multi-leaf collimator (MLC). Part of this thesis deals with the development of control, supervision and verification methods for the scanned proton beam line at the The Svedberg laboratory in Uppsala, Sweden. </p><p>Radiotherapy is preceded by treatment planning, where one of the main objectives is predicting the dose to the patient. The dose is calculated by a dose calculation engine and the accuracy of the results is of course dependent on the accuracy and sophistication of the transport and interaction models of the dose engine itself. But, for the dose distribution calculation to have any bearing on the reality, it needs to be started with relevant input in accordance with the beam that is emitted from the treatment machine. This input is provided by the beam model. As such, the beam model is the link between the reality (the treatment machine) and the treatment planning system. The beam model contains methods to characterise the treatment machine and provides the dose calculation with the reconstructed beam phase space, in some convenient representation. In order for a beam model to be applicable in a treatment planning system, its methods have to be general. </p><p>In this thesis, a beam model for a scanned proton beam is developed. The beam model contains models and descriptions of the beam modifying elements of a scanned proton beam line. Based on a well-defined set of generally applicable characterisation measurements, ten beam model parameters are extracted, describing the basic properties of the beam, i.e. the energy spectrum, the radial and the angular distributions and the nominal direction. Optional beam modifying elements such as a range shifter and an MLC are modelled by dedicated Monte Carlo calculation algorithms. The algorithm that describes the MLC contains a parameterisation of collimator scatter, in which the rather complex phase space of collimator scattered protons has been parameterised by a set of analytical functions. </p><p>Dose calculations based on the phase space reconstructed by the beam model are in good agreement with experimental data. This holds both for the dose distribution of the elementary pencil beam, reflecting the modelling of the basic properties of the scanned beam, as well as for complete calculations of collimated scanned fields.</p>

Traditionally, uncertainties are handled by expanding the irradiated volume to ensure target dose coverage to a certain probability. The uncertainties arise from e.g. the uncertainty in positioning of the patient at every fraction, organ motion and in defining the region of interests on the acquired images. The applied margins are inherently population based and do not exploit the geometry of the individual patient. Probabilistic planning on the other hand incorporates the uncertainties directly into the treatment optimization and therefore has more degrees of freedom to tailor the dose distribution to the individual patient. The aim of this thesis is to create a framework for probabilistic evaluation and optimization based on the concept of dose coverage probabilities. Several computational challenges for this purpose are addressed in this thesis. The accuracy of the fraction by fraction accumulated dose depends directly on the accuracy of the deformable image registration (DIR). Using the simulation framework, we could quantify the requirements on the DIR to 2 mm or less for a 3% uncertainty in the target dose coverage. Probabilistic planning is computationally intensive since many hundred treatments must be simulated for sufficient statistical accuracy in the calculated treatment outcome. A fast dose calculation algorithm was developed based on the perturbation of a pre-calculated dose distribution with the local ratio of the simulated treatment’s fluence and the fluence of the pre-calculated dose. A speedup factor of ~1000 compared to full dose calculation was achieved with near identical dose coverage probabilities for a prostate treatment. For some body sites, such as the cervix dataset in this work, organ motion must be included for realistic treatment simulation. A statistical shape model (SSM) based on principal component analysis (PCA) provided the samples of deformation. Seven eigenmodes from the PCA was sufficient to model the dosimetric impact of the interfraction deformation. A probabilistic optimization method was developed using constructs from risk management of stock portfolios that enabled the dose planner to request a target dose coverage probability. Probabilistic optimization was for the first time applied to dataset from cervical cancer patients where the SSM provided samples of deformation. The average dose coverage probability of all patients in the dataset was within 1% of the requested.

Scanned proton beams offer the possibility to take full advantage of the dose deposition properties of proton beams, i.e. the limited range and sharp peak at the end of the range, the Bragg peak. By actively scanning the proton beam, laterally by scanning magnets and longitudinally by shifting the energy, the position of the Bragg peak can be controlled in all three dimensions, thereby enabling high dose delivery to the target volume only. A typical scanned proton beam line consists of a pair of scanning magnets to perform the lateral beam scanning and possibly a range shifter and a multi-leaf collimator (MLC). Part of this thesis deals with the development of control, supervision and verification methods for the scanned proton beam line at the The Svedberg laboratory in Uppsala, Sweden. Radiotherapy is preceded by treatment planning, where one of the main objectives is predicting the dose to the patient. The dose is calculated by a dose calculation engine and the accuracy of the results is of course dependent on the accuracy and sophistication of the transport and interaction models of the dose engine itself. But, for the dose distribution calculation to have any bearing on the reality, it needs to be started with relevant input in accordance with the beam that is emitted from the treatment machine. This input is provided by the beam model. As such, the beam model is the link between the reality (the treatment machine) and the treatment planning system. The beam model contains methods to characterise the treatment machine and provides the dose calculation with the reconstructed beam phase space, in some convenient representation. In order for a beam model to be applicable in a treatment planning system, its methods have to be general. In this thesis, a beam model for a scanned proton beam is developed. The beam model contains models and descriptions of the beam modifying elements of a scanned proton beam line. Based on a well-defined set of generally applicable characterisation measurements, ten beam model parameters are extracted, describing the basic properties of the beam, i.e. the energy spectrum, the radial and the angular distributions and the nominal direction. Optional beam modifying elements such as a range shifter and an MLC are modelled by dedicated Monte Carlo calculation algorithms. The algorithm that describes the MLC contains a parameterisation of collimator scatter, in which the rather complex phase space of collimator scattered protons has been parameterised by a set of analytical functions. Dose calculations based on the phase space reconstructed by the beam model are in good agreement with experimental data. This holds both for the dose distribution of the elementary pencil beam, reflecting the modelling of the basic properties of the scanned beam, as well as for complete calculations of collimated scanned fields.

The concentrations of some drug solutions are often expressed as ratios or percentages. This system simplified prescription and dispensing when Imperial measures such as grains and minims were used. Ampoules of powerful vasoactive drugs such as catecholamines and potentially toxic local anaesthetics are still labelled as ratios and percentages, seemingly through habit or tradition than for any useful clinical reason. This thesis argues that adherence to this outdated system is confusing, causes drug administration errors, and puts patients at risk. Internet-based questionnaires were used to quantify medical students’ and doctors’ understanding of ratios and percentages. A substantial minority of almost 3000 doctors could not convert between ratios, percentages and mass concentration correctly, made dosing errors of up to three orders of magnitude in written clinical scenarios, and struggled with conversions between metric units. These findings are strong arguments for expressing drug concentrations as mass concentration and providing better drug administration teaching. High fidelity patient simulation was used to examine the influence of clearer ampoule labelling and intensive drug administration teaching. This allowed critical incidents to be reproduced realistically, clinical performances to be assessed, and outcome measures to be accurately recorded. Randomised controlled trials were conducted that demonstrated positive influences of both interventions for doctors and students. The difficulties that nurses encounter when preparing infusions of these drugs on critical care units were also studied and are reported. The findings presented should be sufficient to persuade regulatory authorities to remove ratios and percentages from ampoule labels – a straightforward, cheap, commonsense intervention. The lack of effective clinical error reporting systems and the extreme practical difficulties of conducting clinical trials in this field mean that a firm link between this intervention and patient outcome is unlikely ever to be made, but this should not be an excuse for maintaining the status quo.

Ces travaux portent sur l'optimisation de la planification en radiothérapie prostatique et ORL. De façon à améliorer le calcul dosimétrique, la méthode de calcul de dose dite « Pencil beam » a d'abord été modifiée en considérant un système de coordonnées sphériques, en améliorant le mode de correction des hétérogénéités et en accélérant le calcul en effectuant les opérations de convolution grâce à la transformée de Fourier rapide. L'approche proposée a été comparée aux méthodes classiques en utilisant différents fantômes numériques. Cette évaluation a démontré la précision de la méthode proposée ainsi que l'accélération des calculs d'un facteur 40 par la méthode utilisant la transformée de Fourier, au prix toutefois d'une dégradation de la précision des résultats. Dans un second temps, l'incorporation de critères biologiques lors de l'optimisation du plan de traitement a été mise en œuvre à travers l'équivalent convexe du modèle NTCP (probabilité de toxicité des tissus sains) et son optimisation. L'évaluation de cette approche a été réalisée sur les données de dix patients traités pour un cancer de la prostate et a montré que la méthode proposée produit des planifications cliniquement satisfaisantes avec de meilleurs résultats en termes de toxicité prédite. Une méthode de compensation des incertitudes géométriques survenant lors du traitement a aussi été proposée, reposant sur une décomposition en séries de Taylor et un filtre de Butterworth. Son évaluation a montré son efficacité en termes de réduction des oscillations de haute fréquence ainsi que de présence de points chauds et froids. Enfin, dans un contexte de radiothérapie adaptative en ORL, une étude permettant d'identifier le scénario optimal de replanification, c'est-à-dire le nombre et les moments des replanifications, a été menée. Les critères de comparaison considérés reposaient sur le calcul de la dose cumulée reçue notamment par les parotides lors du traitement complet. L'efficacité des replanifications a ainsi été démontrée, avec par exemple une diminution du risque de toxicité de 9% pour le scénario optimal. Les perspectives de ce travail concernent la combinaison de ces méthodes dans un processus complet de planification pour évaluer leur impact dans un contexte clinique. / This work focuses on the optimization of planning in prostate and head-and-neck radiation therapy. In order to improve the dose calculation, the Pencil Beam method was firstly modified by considering a spherical coordinate system, by improving the heterogeneities correction method and by accelerating the calculation by performing the convolution operations using the Fast Fourier Transform. The proposed approach was compared to conventional methods using different numerical phantoms. This evaluation demonstrated the accuracy of the proposed method and the acceleration of the calculations by a factor 40 by the method using the Fast Fourier Transform, but at the cost of deterioration in the accuracy of the results. In a second step, the incorporation of biological criteria in the optimization of the treatment plan has been implemented through an equivalent convex NTCP constraints and its optimization. The evaluation of this approach has been performed on the data of ten patients treated for prostate cancer and has shown that the proposed method produces clinically satisfactory plans with better results in terms of predicted toxicity. A method to compensate geometric uncertainties occurring during treatment has also been proposed, based on the expansion in series of Taylor and a Butterworth filter. Its evaluation has shown its effectiveness in reducing high-frequency oscillations as well as the presence of hot and cold spots. Finally, in the context of adaptive radiotherapy in head and neck, a study was conducted to identify the optimal scenario of replannings, i.e. the number and timing of replannings. The comparison criteria were based on the calculation of the cumulative dose received by the parotid during the whole treatment. The effectiveness of the replanning has been demonstrated, for example with a decreased risk of toxicity 9% for the optimal scenario. The perspectives of this work relate to the combination of these methods in a comprehensive planning process to assess their clinical impact.

Radiotherapy delivered using scanned beams of protons enables greater conformity between the dose distribution and the tumour than conventional radiotherapy using X rays. However, the dose distributions are more sensitive to changes in patient anatomy, and tend to deteriorate in the presence of motion. Online dose calculation during treatment delivery offers a way of monitoring the delivered dose in real time, and could be used as a basis for mitigating the effects of motion. The aim of this work has therefore been to investigate how the computational power offered by graphics processing units can be harnessed to enable fast analytical dose calculation for online monitoring in proton therapy. The first part of the work consisted of a systematic investigation of various approaches to implementing the most computationally expensive step of the pencil beam algorithm to run on graphics processing units. As a result, it was demonstrated how the kernel superposition operation, or convolution with a spatially varying kernel, can be efficiently implemented using a novel scatter-based approach. For the intended application, this outperformed the conventional gather-based approach suggested in the literature, permitting faster pencil beam dose calculation and potential speedups of related algorithms in other fields. In the second part, a parallelised proton therapy dose calculation engine employing the scatter-based kernel superposition implementation was developed. Such a dose calculation engine, running all of the principal steps of the pencil beam algorithm on a graphics processing unit, had not previously been presented in the literature. The accuracy of the calculation in the high- and medium-dose regions matched that of a clinical treatment planning system whilst the calculation was an order of magnitude faster than previously reported. Importantly, the calculation times were short, both compared to the dead time available during treatment delivery and to the typical motion period, making the implementation suitable for online calculation. In the final part, the beam model of the dose calculation engine was extended to account for the low-dose halo caused by particles travelling at large angles with the beam, making the algorithm comparable to those in current clinical use. By reusing the workflow of the initial calculation but employing a lower resolution for the halo calculation, it was demonstrated how the improved beam model could be included without prohibitively prolonging the calculation time. Since the implementation was based on a widely used algorithm, it was further predicted that by careful tuning, the dose calculation engine would be able to reproduce the dose from a general beamline with sufficient accuracy. Based on the presented results, it was concluded that, by using a single graphics processing unit, dose calculation using the pencil beam algorithm could be made sufficiently fast for online dose monitoring, whilst maintaining the accuracy of current clinical systems.