Radiotherapy is a potential curative option for liver cancer; however, respiratory motion creates uncertainty in treatment delivery. Advances in imaging and registration techniques can provide information regarding changes in respiratory motion. Currently image registration is challenged by computation and manual intervention. A Navigator Channel (NC) technique was developed to overcome these limitations. A population motion model was generated to predict patient-specific motion, while a point motion detection technique was developed to calculate the patient-specific liver edge motion from images. An adaptation technique uses the relative difference between the population and patient calculated liver edge motion to determine the patient's liver volume motion. The NC technique was tested on patient 4D-CT images for initial validation to determine the accuracy. Accuracy was less than 0.10 mm in liver edge detection and approximately 0.25 cm in predicting patient-specific motion. This technique can be used to ensure accurate treatment delivery for liver radiotherapy.

Radiotherapy is a potential curative option for liver cancer; however, respiratory motion creates uncertainty in treatment delivery. Advances in imaging and registration techniques can provide information regarding changes in respiratory motion. Currently image registration is challenged by computation and manual intervention. A Navigator Channel (NC) technique was developed to overcome these limitations. A population motion model was generated to predict patient-specific motion, while a point motion detection technique was developed to calculate the patient-specific liver edge motion from images. An adaptation technique uses the relative difference between the population and patient calculated liver edge motion to determine the patient's liver volume motion. The NC technique was tested on patient 4D-CT images for initial validation to determine the accuracy. Accuracy was less than 0.10 mm in liver edge detection and approximately 0.25 cm in predicting patient-specific motion. This technique can be used to ensure accurate treatment delivery for liver radiotherapy.

Objectives. The goal in radiotherapy is to deliver adequate radiation to the tumor volume while limiting damage to the surrounding healthy tissue. However, this goal is challenged by respiratory-induced motion. The objective of this work was to identify whether motion in electronic portal images can be tracked with an optical flow algorithm and whether a neural network can predict tumor motion. Methods. A multi-resolution optical flow algorithm that incorporates weighting based on the differences between image frames was used to automatically sample the vectors corresponding to the motion. The global motion was obtained by computing the average weighted mean from the set of vectors. The algorithm was evaluated using tumor trajectories taken from seven lung cancer patients, a 3D printed patient tumor and a virtual dynamic multi-leaf collimator (DMLC) system. The feasibility of detecting and tracking motion at the field edge was examined with a proof-of-concept implementation that included (1) an algorithm that detected local motion, and (2) a control algorithm that adapted the virtual MLC. To compensate for system latency, a generalized neural network, using both offline (treatment planning data) and online (during treatment delivery) learning, was implemented for tumor motion prediction. Results and Conclusions. The algorithm tracked the global motion of the target with an accuracy of around 0.5 mm. While the accuracy is similar to other methods, this approach does not require manual delineation of the target and can, therefore, provide real-time autonomous motion estimation during treatment. Motion at the treatment field edge was tracked with an accuracy of -0.4 ± 0.3 mm. This proof-of-concept simulation demonstrated that it is possible to adapt MLC leaves based on the motion detected at the field edges. Unplanned intrusions of external organs-at-risk could be shielded. A generalized network with a prediction error of 0.59 mm, and a shorter initial learning period (compared to previous studies) was achieved. This network may be used as a plug-and-play predictor in which tumor position could be predicted at the start of treatment and the need for pretreatment data and optimization for individual patients may be avoided. / February 2017

<p>In this project several tests were performed to evaluate the performance of an On-Board Imager® (OBI) mounted on a clinical linear accelerator. The measurements were divided into three parts; geometric accuracy, image registration and couch shift accuracy, and image quality. A cube phantom containing a radiation opaque marker was used to study the agreement with treatment isocenter for both kV-images and cone-beam CT (CBCT) images. The long term stability was investigated by acquiring frontal and lateral kV images twice a week over a 3 month period. Stability in vertical and longitudinal robotic arm motion as well as the stability of the center-of-rotation was evaluated. Further, the agreement of kV image and CBCT center with MV image center was examined.</p><p>A marker seed phantom was used to evaluate and compare the three applications in image registration; 2D/2D, 2D/3D and 3D/3D. Image registration using kV-kV image sets were compared with MV MV and MV-kV image sets. Further, the accuracy in 2D/2D matches with images acquired at non-orthogonal gantry angles was evaluated. The image quality in CBCT images was evaluated using a Catphan® phantom. Hounsfield unit (HU) uniformity and linearity was compared with planning CT. HU accuracy is crucial for dose verification using CBCT data.</p><p>The geometric measurements showed good long term stability and accurate position reproducibility after robotic arm motions. A systematic error of about 1 mm in lateral direction of the kV-image center was detected. A small difference between kV and CBCT center was observed and related to a lateral kV detector offset. The vector disagreement between kV- and MV-image centers was  2 mm at some gantry angles. Image registration with the different match applications worked sufficiently. 2D/3D match was seen to correct more accurately than 2D/2D match for large translational and rotational shifts. CBCT images acquired with full-fan mode showed good HU uniformity but half fan images were less uniform. In the soft tissue region the HU agreement with planning CT was reasonable while a larger disagreement was observed at higher densities. This work shows that the OBI is robust and stable in its performance. With regular QC and calibrations the geometric precision of the OBI can be maintained within 1 mm of treatment isocenter.</p>

In this project several tests were performed to evaluate the performance of an On-Board Imager® (OBI) mounted on a clinical linear accelerator. The measurements were divided into three parts; geometric accuracy, image registration and couch shift accuracy, and image quality. A cube phantom containing a radiation opaque marker was used to study the agreement with treatment isocenter for both kV-images and cone-beam CT (CBCT) images. The long term stability was investigated by acquiring frontal and lateral kV images twice a week over a 3 month period. Stability in vertical and longitudinal robotic arm motion as well as the stability of the center-of-rotation was evaluated. Further, the agreement of kV image and CBCT center with MV image center was examined. A marker seed phantom was used to evaluate and compare the three applications in image registration; 2D/2D, 2D/3D and 3D/3D. Image registration using kV-kV image sets were compared with MV MV and MV-kV image sets. Further, the accuracy in 2D/2D matches with images acquired at non-orthogonal gantry angles was evaluated. The image quality in CBCT images was evaluated using a Catphan® phantom. Hounsfield unit (HU) uniformity and linearity was compared with planning CT. HU accuracy is crucial for dose verification using CBCT data. The geometric measurements showed good long term stability and accurate position reproducibility after robotic arm motions. A systematic error of about 1 mm in lateral direction of the kV-image center was detected. A small difference between kV and CBCT center was observed and related to a lateral kV detector offset. The vector disagreement between kV- and MV-image centers was  2 mm at some gantry angles. Image registration with the different match applications worked sufficiently. 2D/3D match was seen to correct more accurately than 2D/2D match for large translational and rotational shifts. CBCT images acquired with full-fan mode showed good HU uniformity but half fan images were less uniform. In the soft tissue region the HU agreement with planning CT was reasonable while a larger disagreement was observed at higher densities. This work shows that the OBI is robust and stable in its performance. With regular QC and calibrations the geometric precision of the OBI can be maintained within 1 mm of treatment isocenter.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19225号 / 医博第4024号 / 新制||医||1010(附属図書館) / 32224 / 京都大学大学院医学研究科医学専攻 / (主査)教授 戸井 雅和, 教授 富樫 かおり, 教授 一山 智 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DGAM

To improve relatively poor outcomes for locally-advanced lung cancer patients, many current efforts are dedicated to minimizing uncertainties in radiotherapy. This enables the isotoxic delivery of escalated tumor doses, leading to better local tumor control. The current dissertation specifically addresses inter-fractional uncertainties resulting from patient setup variability. An automatic block-matching registration (BMR) algorithm is implemented and evaluated for the purpose of directly localizing advanced-stage lung tumors during image-guided radiation therapy. In this algorithm, small image sub-volumes, termed “blocks”, are automatically identified on the tumor surface in an initial planning computed tomography (CT) image. Each block is independently and automatically registered to daily images acquired immediately prior to each treatment fraction. To improve the accuracy and robustness of BMR, this algorithm incorporates multi-resolution pyramid registration, regularization with a median filter, and a new multiple-candidate-registrations technique. The result of block-matching is a sparse displacement vector field that models local tissue deformations near the tumor surface. The distribution of displacement vectors is aggregated to obtain the final tumor registration, corresponding to the treatment couch shift for patient setup correction. Compared to existing rigid and deformable registration algorithms, the final BMR algorithm significantly improves the overlap between target volumes from the planning CT and registered daily images. Furthermore, BMR results in the smallest treatment margins for the given study population. However, despite these improvements, large residual target localization errors were noted, indicating that purely rigid couch shifts cannot correct for all sources of inter-fractional variability. Further reductions in treatment uncertainties may require the combination of high-quality target localization and adaptive radiotherapy.

The purpose of this thesis is to validate the Monte Carlo algorithm for electron radiotherapy in the Eclipse™ treatment planning system (TPS), and to compare the accuracy of the Electron Monte Carlo algorithm (eMC) to the Pencil Beam algorithm (PB) in Eclipse™. Dose distributions from GafChromic™ EBT3 film measurements were compared to dose distributions from eMC and PB treatment plans. Measurements were obtained with 6MeV, 9MeV, and 12MeV electron beams at various depths. A 1 cm thick solid water template with holes for bone-like and lung-like plugs was used to create assorted configurations and heterogeneities. Dose distributions from eMC plans agreed better with the film measurements based on gamma analysis. Gamma values for eMC were between 83%-99%, whereas gamma values for PB treatment plans were as low as 38.66%. Our results show that using the eMC algorithm will improve dose accuracy in regions with heterogeneities and should be considered over PB. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Ce travail de thèse porte sur la quantification et la prise en compte des variations anatomiques en cours de radiothérapie guidée par l'image pour le cancer de la prostate. Nous proposons tout d'abord une approche basée population pour quantifier et analyser les incertitudes géométriques, notamment à travers des matrices de probabilité de présence de la cible en cours de traitement. Nous proposons ensuite une méthode d'optimisation des marges suivant des critères de couverture géométrique de la cible tumorale. Cette méthode permet d'obtenir des marges objectives associées aux différents types d'incertitudes géométriques et aux différentes modalités de repositionnement du patient. Dans un second temps, nous proposons une méthode d'estimation de la dose cumulée reçue localement par les tissus pendant un traitement de radiothérapie de la prostate. Cette méthode repose notamment sur une étape de recalage d'images de façon à estimer les déformations des organes entre les séances de traitement et la planification. Différentes méthodes de recalage sont proposées, suivant les informations disponibles (délinéations ou points homologues) pour contraindre la déformation estimée. De façon à évaluer les méthodes proposées au regard de l'objectif de cumul de dose, nous proposons ensuite la génération et l'utilisation d'un fantôme numérique reposant sur un modèle biomécanique des organes considérés. Les résultats de l'approche sont présentés sur ce fantôme numérique et sur données réelles. Nous montrons ainsi que l'apport de contraintes géométriques permet d'améliorer significativement la précision du cumul et que la méthode reposant sur la sélection de contraintes ponctuelles présente un bon compromis entre niveau d'interaction et précision du résultat. Enfin, nous abordons la question de l'analyse de données de populations de patients dans le but de mieux comprendre les relations entre dose délivrée localement et effets cliniques. Grâce au recalage déformable d'une population de patients sur une référence anatomique, les régions dont la dose est significativement liée aux événements de récidive sont identifiées. Il s'agit d'une étude exploratoire visant à terme à mieux exploiter l'information portée par l'intégralité de la distribution de dose, et ce en fonction du profil du cancer. / This work deals with the quantification and the compensation of anatomical deformations during image-guided radiotherapy of prostate cancer. Firstly, we propose a population-based approach to quantify the geometrical uncertainties by means of coverage probability matrices of the target tumor during the treatment. We then propose a margins optimization method based on geometrical coverage criteria of the tumor target. This method provides rationnal margins models associated to the different geometrical uncertainties and patient repositioning protocols. Secondly, we propose a method to estimate the locally accumulated dose during the treatment. This method relies on a deformable image registration process in order to estimate the organ deformations between each treatment fraction and the planning. Different registration methods are proposed, using different level of user interactions (landmarks specification or delineations) to constrain the deformation estimation. In order to evaluate the performance of the proposed methods, we then describe the generation of a numerical phantom based on a biomechanical model. The results are presented for the numerical phantom and real clinical cases. We show that the benefit brought by the manual placement of some landmarks to constrain the registration represents a good compromise between the required interaction level and the dose estimation accuracy. Finally, we address the issue of the analysis of population data in order to better understand the relationship between the locally delivered dose and clinical effects. With deformable image registration of a population of patients on an anatomical template, regions whose dose is significantly associated with recurrence events are identified. This last part is an exploratory study aiming to better use the information carried by the entire distribution dose, and according to the cancer profile.

Es wird erwartet, dass die Integration der Magnetresonanztomografie (MRT) in die Protonentherapie die Treffgenauigkeit bei der Strahlentherapie für Krebserkrankungen deutlich verbessern wird. Besonders für Tumoren in beweglichen Organen des Thorax oder des Abdomens könnte die MRT-integrierte Protonentherapie (MRiPT) eine Synchronisierung der Bestrahlung mit der Tumorposition ermöglichen, was zu einer verminderten Normalgewebsdosis und weniger Nebenwirkungen führen könnte. Bis heute ist solch eine Integration jedoch aufgrund fehlender Studien zu potenziellen gegenseitigen Störeinflüssen dieser beiden Systeme nicht vollzogen worden. Diese Arbeit widmete sich zwei solcher Störeinflüsse, und zwar der Ablenkung des Protonenstrahls im Magnetfeld des MRT- Scanners, und umgekehrt, dem Einfluss der elekromagnetischen Felder der Protonentherapieanlage und des Protonenstrahls selbst auf die MRT-Bilder. Obwohl vorangegangene Studien den derzeitigen Konsens aufgezeigt haben, dass die Trajektorie eines abgebremsten Protonenstrahls im homogenen Phantom in einem transversalen Magnetfeld vorhersagbar ist, zeigte sich im quantitativen Vergleich der publizierten Modelle, der im ersten Teil dieser Arbeit vorgestellt wurde, dass die Vorhersagen dieser Modelle nur für eine begrenzte Anzahl von Kombinationen aus Magnetfeldstärke und Protonenenergie übereinstimmen. Die Schwächen bestehender analytischer Modelle wurden deshalb analysiert und quantifiziert. Kritische Annahmen und die mangelnde Anwendbarkeit auf realistische, d.h. inhomogene Magnetfeldstärken und Patientengeometrien wurden als Hauptprobleme identifiziert. Um diese zu überwinden, wurde ein neues semianalytisches Modell namens RAMDIM entwickelt. Es wurde gezeigt, dass dieses auf realistischere Fälle anwendbar und genauer ist als existierende analytische Modelle und dabei schneller als Monte-Carlo-basierte Teilchenspursimulationen. Es wird erwartet, dass dieses Modell in der MRiPT Anwendung findet zur schnellen und genauen Ablenkungsberechnung, zur Betrahlungsplanoptimierung und bei der MRT-geführten Strahlnachführung. In einem zweiten Schritt wurde die magnetfeldinduzierte Protonenstrahlablenkung in einem gewebeähnlichen Material durch Filmdosimetrie erstmalig gemessen und mit Monte-Carlo-Simulationen verglichen. In einem transversalen Magnetfeld einer Flussdichte von 0,95 T wurde experimentell gezeigt, dass die laterale Versetzung des Bragg-Peaks für Protonenenergien zwischen 80 und 180 MeV in PMMA zwischen 1 und 10 mm liegt. Die Retraktion des Bragg-Peaks war ≤ 0,5 mm. Es wurde gezeigt, dass die gemessene Versetzung des Bragg-Peaks innerhalb von 0,8 mm mit Monte-Carlo-basierten Vorhersagen übereinstimmt. Diese Ergebnisse weisen darauf hin, dass die Protonenstrahlablenkung durch Monte-Carlo-Simulationen genau vorhersagbar ist und damit der Realisierbarkeit der MRiPT nicht im Wege steht. Im zweiten Teil dieser Arbeit wurde erstmalig ein MRT-Scanner in eine Protonenstrahlführung integriert. Hierfür wurde ein offener Niederfeld-MRT-Scanner am Ende einer statischen Forschungsstrahlführung einer Protonentherapieanlage platziert. Die durch das statische Magnetfeld des MRT-Scanners hervorgerufene Strahlablenkung wurde bei der Ausrichtung des MRT-Scanners berücksichtigt. Die sequenzabhängigen, veränderlichen Gradientenfelder hatten keinen messbaren Einfluss auf das transversale Strahlprofil hinter dem MRT-Scanner. Die Magnetfeldhomogenität des Scanners lag innerhalb der Herstellervorgaben und zeigte keinen relevanten Einfluss von Rotationen der Protonengantry im benachbarten Bestrahlungsraum. Eine magnetische Abschirmung war zum gleichzeitigen Betrieb des MRT-Scanners und der Protonentherapieanlage nicht notwendig. Dies beweist die Machbarkeit gleichzeitiger Bestrahlung und Bildgebung in einem ersten MRiPT Aufbau. Die MRT-Bildqualität des Aufbaus wurde darauffolgend anhand eines angepassten Standardprotokolls aus Spin-Echo- und Gradienten-Echo-Sequenzen quantifiziert und es wurde gezeigt, dass die Bildqualität sowohl ohne als auch mit gleichzeitiger Bestrahlung hinreichend ist. Alle bestimmten geometrischen Parameter stimmten mit den physikalischen Abmessungen des verwendeten Phantoms innerhalb eines Bildpixels überein. Wie es für Niederfeld-MRT-Scanner üblich ist, war das Signal-Rausch-Verhältnis (SNR) der MRT-Bilder gering, was im Vergleich zu den Standardkriterien zu einer geringen Bildhomogenität und zu einem hohen Geisterbildanteil im Bild führte. Außerdem wurde aufgrund von Unsicherheiten in der Hochfrequenzkalibrierung des MRT-Scanners eine starke Schwankung der vertikalen Phantomposition mit einem Interquartilabstand von bis zu 1,5 mm beobachtet. T2*-gewichtete Gradientenechosequenzen zeigten zudem aufgrund von Magnetfeldinho- mogenitäten relevante ortsabhängige Bildverzerrungen. Es wurde gezeigt, dass die meisten Bildqualitätsparameter mit und ohne gleichzeitige Betrahlung äquivalent sind. Es wurde jedoch ein signifikanter Betrahlungseinfluss in Form von einer vertikalen Bildverschiebung und einer Verminderung des SNR beobachtet, die durch eine Änderung im Magnetfeld des MRT-Scanners erklärt werden können, welche durch zu diesem Feld parallel ausgerichtete Komponenten im Fernfeld der Strahlführungsmagneten hervorgerufen wird. Während das verminderte SNR vermutlich irrelevant ist (Dif- ferenz im Median ≤ 1,5), ist die sequenzabhängige Bildverschiebung (Differenz im Median bis zu 0,7 mm) nicht immer vernachlässigbar. Diese Ergebisse zeigen, dass die MRT-Bilder durch gleichzeitige Bildgebung nicht schwerwiegend verfälscht werden, dass aber eine dedizierte Optimierung der Hochfrequenzkalibrierung und der MRT-Bildsequenzen notwendig ist. Im letzten Teil der Arbeit wurde gezeigt, dass ein stromabhängiger Einfluss des Protonenstrahls auf MRT-Bilder eines Wasserphantoms durch zwei verschiedene MRT-Sequenzen messbar gemacht und zur Reichweiteverifikation genutzt werden kann. Der Effekt war in verschiedenen Flüssigkeiten, jedoch nicht in viskosen und festen Materialen, nachweisbar und wurde auf Hitzekonvektion zurückgeführt. Es wird erwartet, dass diese Methode in der MRiPT für Konstanztests der Protonenreichweite bei der Maschinenqualitätssicherung nützlich sein wird. Zusammenfassend hat diese Arbeit die Genauigkeit der Vorhersage der Strahlablenkung quantifiziert und verbessert, sowie Potenzial und Realisierbarkeit einer gleichzeitigen MRT-Bildgebung und Protonenbestrahlung gezeigt. Die weitere Entwicklung eines ersten MRiPT-Prototyps ist demnach gerechtfertigt.:List of Figures v List of Tables vii 1 General Introduction 1 2 State of the Art: Proton Therapy and Magnetic Resonance Imaging 3 2.1 Proton Therapy 4 2.1.1 Physical Principle 4 2.1.2 Beam Delivery 7 2.1.3 Motion Management and the Role of Image Guidance 10 2.2 Magnetic Resonance Imaging 14 2.2.1 Physical Principle 14 2.2.2 Image Generation by Pulse Sequences 18 2.2.3 Image Quality 21 2.3 MR-Guided Radiotherapy 24 2.3.1 Offline MR Guidance 24 2.3.2 On-line MR Guidance 25 2.4 MR-Integrated Proton Therapy 28 2.4.1 Aims of this Thesis 32 3 Magnetic Field-Induced Beam Deflection and Bragg Peak Displacement 35 3.1 Analytical Description 36 3.1.1 Review of Analytical Models 36 3.1.2 New Model Formulation 41 3.1.3 Evaluation of Analytical and Numerical Models 44 3.1.4 Discussion 51 3.2 Monte Carlo Simulation and Experimental Verification 54 3.2.1 Verification Setup 54 3.2.2 Monte Carlo Simulation 56 3.2.3 Experimental Verification 60 3.2.4 Discussion 61 3.3 Summary 63 4 Integrated In-Beam MR System: Proof of Concept 65 4.1 Integration of a Low-Field MR Scanner and a Static Research Beamline 65 4.1.1 Proton Therapy System 66 4.1.2 MR Scanner 66 4.1.3 Potential Sources of Interference 67 4.1.4 Integration of Both Systems 68 4.2 Beam and Image Quality in the Integrated Setup 70 4.2.1 Beam Profile 70 4.2.2 MR Magnetic Field Homogeneity 72 4.2.3 MR Image Quality - Qualitative In Vivo and Ex Vivo Test 74 4.2.4 MR Image Quality - Quantitative Phantom Tests 77 4.3 Feasibility of MRI-based Range Verification 86 4.3.1 MR Sequences 86 4.3.2 Proton Beam Parameters 88 4.3.3 Target Material Dependence 91 4.3.4 Discussion 92 4.4 Summary 96 5 Discussion and Future Perspectives 99 6 Summary/Zusammenfassung 105 6.1 Summary 105 6.2 Zusammenfassung 108 Bibliography I Supplementary Information XXIX A Beam Deflection: Experimental Measurements XXIX A.1 Setup XXIX A.2 Film Handling and Evaluation XXX A.3 Uncertainty Estimation XXX B Beam Deflection: Monte Carlo Simulations XXXIII B.1 Magnetic Field Model XXXIII B.2 Uncertainty Estimation XXXIV C Integrated MRiPT Setup XXXVI C.1 Magnetic Field Map XXXVI C.2 Sequence Parameters XXXVI C.3 Image Quality Parameters XLII C.4 Range Verification Sequences XLII / The integration of magnetic resonance imaging (MRI) into proton therapy is expected to strongly increase the targeting accuracy in radiation therapy for cancerous diseases. Especially for tumours situated in mobile organs in the thorax and abdomen, MR-integrated proton therapy (MRiPT) could enable the synchronisation of irradiation to the tumour position, resulting in less dose to normal tissue and reduced side effects. However, such an integration has been hindered so far by a lack of scientific studies on the potential mutual interference between the two components. This thesis was dedicated to two of these sources of interference, namely the deflection of the proton beam by the magnetic field of the MR scanner and, vice versa, alterations of the MR image induced by the electromagnetic fields of the proton therapy facility and by the beam itself. Although previous work has indicated that there is general consensus that the trajectory of a slowing down proton beam in a homogeneous phantom inside a transverse magnetic field is predictable, a quantitative comparison of the published methods, as presented in the first part of this thesis, has shown that predictions of different models only agree for certain proton beam energies and magnetic flux densities. Therefore, shortcomings of previously published analytical methods have been analysed and quantified. The inclusion of critical assumptions and the lack of applicability to realistic, i.e. non-uniform, magnetic flux densities and patient anatomies have been identified as main problems. To overcome these deficiencies, a new semi-analytical model called RAMDIM has been developed. It was shown that this model is both applicable to more realistic setups and less assumptive than existing analytical approaches, and faster than Monte Carlo based particle tracking simulations. This model is expected to be useful in MRiPT for fast and accurate deflection estimations, treatment plan optimisation, and MR-guided beam tracking. In a second step, the magnetic field-induced proton beam deflection has been measured for the first time in a tissue-mimicking medium by film dosimetry and has been compared against Monte Carlo simulations. In a transverse magnetic field of 0.95 T, it was experimentally shown that the lateral Bragg peak displacement ranges between 1 mm and 10 mm for proton energies between 80 and 180 MeV in PMMA. Range retraction was found to be ≤ 0.5 mm. The measured Bragg peak displacement was shown to agree within 0.8 mm with Monte Carlo simulations. These results indicate that proton beam deflection in a homogeneous medium is accurately predictable for intermediate proton beam energies and magnetic flux densities by Monte Carlo simulations and therefore not impeding the feasibility of MRiPT. In the second part of this thesis, an MR scanner has been integrated into a proton beam line for the first time. For this purpose, an open low-field MR scanner has been placed at the end of a fixed horizontal proton research beam line in a proton therapy facility. The beam deflection induced by the static magnetic field of the scanner was taken into account for alignment of the beam and the FOV of the scanner. The pulse sequence-dependent dynamic gradient fields did not measurably affect the transverse beam profile behind the MR scanner. The MR magnetic field homogeneity was within the vendor’s specifications and not relevantly influenced by the rotation of the proton gantry in the neighbouring treatment room. No magnetic field compensation system was required for simultaneous operation of the MR scanner and the proton therapy system. These results proof that simultaneous irradiation and imaging is feasible in an in-beam MR setup. The MR image quality of the in-beam MR scanner was then quantified by an adapted standard protocol comprising spin and gradient echo imaging and shown to be acceptable both with and without simultaneous proton beam irradiation. All geometrical parameters agreed with the mechanical dimensions of the used phantom within one pixel width. As common for low-field MR scanners, the signal-to-noise ratio (SNR) of the MR images was low, which resulted in a low image uniformity and a high ghosting ratio in comparison to the standardised test criteria. Furthermore, a strong fluctuation of the vertical phantom position due to uncertainties in the pre-scan frequency calibration was observed, with an interquartile range of up to 1.5 mm. T2*-weighted gradient echo images showed relevant nonuniform deformations due to magnetic field inhomogeneities. Most image quality parameters were shown to be equivalent with and without simultaneous proton beam irradiation. However, a significant influence of simultaneous irradiation was observed as a shift of the vertical phantom position and a decrease in the SNR, both of which can be explained by a change in the B0 field of the MR scanner induced by components of the fringe field of the beam line magnets directed parallel to B0 . While the decrease in SNR is not expected to be relevant (median differences were within 1.5 ), the sequence-dependent phantom shift (median differences of up to 0.7 mm) can become non-negligible. These results show that the MR images are not severely distorted by simultaneous irradiation, but a dedicated optimisation of the pre-scan RF calibration and the MR sequences is required for MRiPT. Lastly, a current-dependent influence of the proton beam on the MR image was shown to be measurable in water in two different MR sequences, which allowed for range verification measurements. The effect was observed in different liquids but not in highly viscose and solid materials, and most probably induced by heat convection. This method is expected to be useful in MRiPT for consistency tests of the proton range during machine-specific quality assurance. In conclusion, this work has improved and quantified the accuracy of beam deflection predictions and shown the feasibility and potential of in-beam MR imaging, justifying further research towards a first MRiPT prototype.:List of Figures v List of Tables vii 1 General Introduction 1 2 State of the Art: Proton Therapy and Magnetic Resonance Imaging 3 2.1 Proton Therapy 4 2.1.1 Physical Principle 4 2.1.2 Beam Delivery 7 2.1.3 Motion Management and the Role of Image Guidance 10 2.2 Magnetic Resonance Imaging 14 2.2.1 Physical Principle 14 2.2.2 Image Generation by Pulse Sequences 18 2.2.3 Image Quality 21 2.3 MR-Guided Radiotherapy 24 2.3.1 Offline MR Guidance 24 2.3.2 On-line MR Guidance 25 2.4 MR-Integrated Proton Therapy 28 2.4.1 Aims of this Thesis 32 3 Magnetic Field-Induced Beam Deflection and Bragg Peak Displacement 35 3.1 Analytical Description 36 3.1.1 Review of Analytical Models 36 3.1.2 New Model Formulation 41 3.1.3 Evaluation of Analytical and Numerical Models 44 3.1.4 Discussion 51 3.2 Monte Carlo Simulation and Experimental Verification 54 3.2.1 Verification Setup 54 3.2.2 Monte Carlo Simulation 56 3.2.3 Experimental Verification 60 3.2.4 Discussion 61 3.3 Summary 63 4 Integrated In-Beam MR System: Proof of Concept 65 4.1 Integration of a Low-Field MR Scanner and a Static Research Beamline 65 4.1.1 Proton Therapy System 66 4.1.2 MR Scanner 66 4.1.3 Potential Sources of Interference 67 4.1.4 Integration of Both Systems 68 4.2 Beam and Image Quality in the Integrated Setup 70 4.2.1 Beam Profile 70 4.2.2 MR Magnetic Field Homogeneity 72 4.2.3 MR Image Quality - Qualitative In Vivo and Ex Vivo Test 74 4.2.4 MR Image Quality - Quantitative Phantom Tests 77 4.3 Feasibility of MRI-based Range Verification 86 4.3.1 MR Sequences 86 4.3.2 Proton Beam Parameters 88 4.3.3 Target Material Dependence 91 4.3.4 Discussion 92 4.4 Summary 96 5 Discussion and Future Perspectives 99 6 Summary/Zusammenfassung 105 6.1 Summary 105 6.2 Zusammenfassung 108 Bibliography I Supplementary Information XXIX A Beam Deflection: Experimental Measurements XXIX A.1 Setup XXIX A.2 Film Handling and Evaluation XXX A.3 Uncertainty Estimation XXX B Beam Deflection: Monte Carlo Simulations XXXIII B.1 Magnetic Field Model XXXIII B.2 Uncertainty Estimation XXXIV C Integrated MRiPT Setup XXXVI C.1 Magnetic Field Map XXXVI C.2 Sequence Parameters XXXVI C.3 Image Quality Parameters XLII C.4 Range Verification Sequences XLII