Bakgrund Extern strålbehandling är en viktig del av processen för behandling av cervikal cancer. Målet med denna typ av behandling är att bestråla tumörområdet med så hög dos som möjligt och omkringliggande frisk vävnad med så lite dos som möjligt. Ett problem som upptäckts är att rörelser i tumörområdet under behandling kan påverka precisionen av strålfältet. Syfte Syftet med litteraturstudien var att beskriva omfattning av rörelse och volymförändring i tumörområdet under strålbehandling av cervikal cancer. Metod                  Nio artiklar med kvantitativ design kvalitetsgranskades och resultaten sammanställdes med inspiration av Fribergs modell. Resultat Omfattning av rörelser och volymförändringar upptäcktes variera och är något som skiljer sig mellan individer. Valet av bildtagnings- och mätmetod har stor betydelse gällande patientsäkerhet och stråldos.   Slutsats Hur mycket tumörområdet rör sig/förändras i volym var något som varierade mellan patienterna i studierna och det är därför viktigt att anpassa behandlingen efter dessa variationer. Olika metoder för bildtagning och mätning kan användas både för att upptäcka rörelser och volymförändringar i tumörområdet under extern strålbehandling. De olika metodernas fördelar bör noggrant vägas mot nackdelar innan användning för att hitta en optimal metod som främjar patientsäkerhet. / Background External radiation therapy is an important part when treating cervical cancer. The goal of this type of therapy is to irradiate the tumor area with the highest possible dose and minimize the dose given to the surrounding healthy tissue. One problem showed is that movement in the tumor area during treatment can cause problems regarding keeping the precision as high as possible. Aim The aim of this literature study was to describe the extent of movement and volume change in the tumor area during external radiotherapy treatment of cervical cancer. Method Nine articles with quantitative design were quality-reviewed and the results were compiled with inspiration from Friberg's model. Results The extent of movements and volume changes was discovered varying and is something that differs between individuals. The choice of imaging and measurement method is of great importance in terms of patient safety and radiation dose. Conclusions The extent of movement and change in volume varied between patients in the studies and it is therefore important to adjust the treatment according to these variations. Different methods of imaging and measurement can be used both to detect movements and volume changes in the tumor area during external radiation therapy. The benefits of the different methods should be carefully weighed against disadvantages before use to find an optimal method that promotes patient safety.

External beam radiation therapy is currently one of the most commonly used modalities for treating cancer. With the rise of new technologies and increasing computational power, machine learning, deep learning and artificial intelligence applications used for classification and regression problems have begun to find their way into the field of radiation oncology. One such application is the automated generation of radiotherapy treatment plans, which must be optimized for every single patient. The department of radiation physics in Lund, Sweden, has developed an autoplanning software, which in combination with a commercially available treatment planning system (TPS), can be used for automatic creation of clinical treatment plans. The parameters of a multivariable cost function are changed iteratively, making it possible to generate a great amount of different treatment plans for a single patient. The output leads to optimal, near-optimal, clinically acceptable or even non-acceptable treatment plans. In this thesis, the possibility of using machine and deep learning to minimize the amount of treatment plans generated by the autoplanning software as well as the possibility of finding cost function parameters that lead to clinically acceptable optimal or near-optimal plans is evaluated. Data augmentation is used to create matrices of optimal treatment plan parameters, which are stored in a training database.  Patient specific training features are extracted from the TPS, as well as from the bottleneck layer of a trained deep neural network autoencoder. The training features are then matched against the same features extracted for test patients, using a k-nearest neighbor algorithm. Finally, treatment plans for a new patient are generated using the output plan parameter matrices of its nearest neighbors. This allows for a reduction in computation time as well as for finding suitable cost function parameters for a new patient.

Le cancer de la prostate est l'un des cancers les plus fréquents chez l'homme. L'un des traitements standard est la radiothérapie externe, qui consiste à délivrer un rayonnement d'ionisation à une cible clinique, en l'occurrence la prostate et les vésicules séminales. Les objectifs de la radiothérapie externe sont la délivrance d'une dose d'irradiation maximale à la tumeur tout en épargnant les organes voisins (principalement le rectum et la vessie) pour éviter des complications suite au traitement. Comprendre les relations dose/toxicité est une question centrale pour améliorer la fiabilité du traitement à l'étape de planification inverse. Des modèles prédictifs de toxicité pour le calcul des probabilités de complications des tissus sains (normal tissue complication probability, NTCP) ont été développés afin de prédire les événements de toxicité en utilisant des données dosimétriques. Les principales informations considérées sont les histogrammes dose-volume (HDV), qui fournissent une représentation globale de la distribution de dose en fonction de la dose délivrée par rapport au pourcentage du volume d'organe. Cependant, les modèles actuels présentent certaines limitations car ils ne sont pas totalement optimisés; la plupart d'entre eux ne prennent pas en compte les informations non-dosimétrique (les caractéristiques spécifiques aux patients, à la tumeur et au traitement). De plus, ils ne fournissent aucune compréhension des relations locales entre la dose et l'effet (dose-espace/effet relations) car ils n'exploitent pas l'information riche des distributions de planification de dose 3D. Dans un contexte de prédiction de l'apparition de saignement rectaux suite au traitement du cancer de la prostate par radiothérapie externe, les objectifs de cette thèse sont : i) d'extraire des informations pertinentes à partir de l'HDV et des variables non-dosimétriques, afin d'améliorer les modèles NTCP existants et ii) d'analyser les corrélations spatiales entre la dose locale et les effets secondaires permettant une caractérisation de la distribution de dose 3D à l'échelle de l'organe. Ainsi, les stratégies visant à exploiter les informations provenant de la planification (distributions de dose 3D et HDV) ont été proposées. Tout d'abord, en utilisant l'analyse en composantes indépendantes, un nouveau modèle prédictif de l'apparition de saignements rectaux, combinant d'une manière originale l'information dosimétrique et non-dosimétrique, a été proposé. Deuxièmement, nous avons mis au point de nouvelles approches visant à prendre conjointement profit des distributions de dose de planification 3D permettant de déceler la corrélation subtile entre la dose locale et les effets secondaires pour classer et/ou prédire les patients à risque de souffrir d'un saignement rectal, et d'identifier les régions qui peuvent être à l'origine de cet événement indésirable. Plus précisément, nous avons proposé trois méthodes stochastiques basées sur analyse en composantes principales, l'analyse en composantes indépendantes et la factorisation discriminante en matrices non-négatives, et une méthode déterministe basée sur la décomposition polyadique canonique de tableaux d'ordre 4 contenant la dose planifiée. Les résultats obtenus montrent que nos nouvelles approches présentent de meilleures performances générales que les méthodes prédictives de la littérature. / Prostate cancer is among the most common types of cancer worldwide. One of the standard treatments is external radiotherapy, which involves delivering ionizing radiation to a clinical target, in this instance the prostate and seminal vesicles. The goal of radiotherapy is to achieve a maximal local control while sparing neighboring organs (mainly the rectum and the bladder) to avoid normal tissue complications. Understanding the dose/toxicity relationships is a central question for improving treatment reliability at the inverse planning step. Normal tissue complication probability (NTCP) toxicity prediction models have been developed in order to predict toxicity events using dosimetric data. The main considered information are dose-volume histograms (DVH), which provide an overall representation of dose distribution based on the dose delivered per percentage of organ volume. Nevertheless, current dose-based models display limitations as they are not fully optimized; most of them do not include additional non-dosimetric information (patient, tumor and treatment characteristics). Furthermore, they do not provide any understanding of local relationships between dose and effect (dose-space/effect relationship) as they do not exploit the rich information from the 3D planning dose distributions. In the context of rectal bleeding prediction after prostate cancer external beam radiotherapy, the objectives of this thesis are: i) to extract relevant information from DVH and non-dosimetric variables, in order to improve existing NTCP models and ii) to analyze the spatial correlations between local dose and side effects allowing a characterization of 3D dose distribution at a sub-organ level. Thus, strategies aimed at exploiting the information from the radiotherapy planning (DVH and 3D planned dose distributions) were proposed. Firstly, based on independent component analysis, a new model for rectal bleeding prediction by combining dosimetric and non-dosimetric information in an original manner was proposed. Secondly, we have developed new approaches aimed at jointly taking advantage of the 3D planning dose distributions that may unravel the subtle correlation between local dose and side effects to classify and/or predict patients at risk of suffering from rectal bleeding, and identify regions which may be at the origin of this adverse event. More precisely, we proposed three stochastic methods based on principal component analysis, independent component analysis and discriminant nonnegative matrix factorization, and one deterministic method based on canonical polyadic decomposition of fourth order array containing planned dose. The obtained results show that our new approaches exhibit in general better performances than state-of-the-art predictive methods.

Submitted by Pedro Silva Filho (pfsilva@ipen.br) on 2017-11-17T17:35:26Z No. of bitstreams: 0 / Made available in DSpace on 2017-11-17T17:35:26Z (GMT). No. of bitstreams: 0 / A utilização da técnica de teleterapia para tratamento de câncer tem sido usada por anos com bons resultados clínicos. Em meados da década de 90, a remoção do filtro aplainador, item que compõe o cabeçote de um acelerador linear de uso clínico, tem sido objeto de estudos por demonstrar bons resultados no tratamento de alguns tipos de câncer. Técnicas utilizadas como Radioterapia de Intensidade Modulada (IMRT) e Radioterapia Estereotáxica (SRT), mostram-se mais eficazes quando não se utiliza o filtro aplainador. A empresa Varian Oncology lançou em 2012 um acelerador linear de uso clínico capaz de operar com o filtro aplainador (FF) e sem o filtro aplainador (FFF), o TrueBeam. Os objetivos desse trabalho são avaliar a homogeneidade de dois importantes parâmetros utilizados para o cálculo de dose nos pacientes submetidos ao tratamento com esse modelo de acelerador linear, a porcentagem de dose profunda (PDP) e índice de qualidade do feixe (TPR20/10). Os dados fornecidos para a análise foram cedidos pelo Hospital Israelita Albert Einstein (HIAE), Real Hospital Português (RHP) e 3 instituições norte-americanas. Através de uma análise estatística dos dados das instituições citadas pode-se observar melhor o comportamento desses parâmetro que demonstraram-se muito homogêneos e com erros menores que 1% na maioria dos casos, confirmando desse modo que os aceleradores lineares do modelo TrueBeam mantém na maioria das vezes uma boa concordância dos parâmetros analisados. / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP

This thesis paper examines the feasibility of using external-beam PIXE to study the surface enrichment effect in metal artifacts. By varying the energy of the incident proton beam, we penetrated the artifact's surface to different levels and were able to produce a depth profile of the elemental composition of the sample. In this study, the sample set we chose to examine consisted of ancient and modern coins. This paper first describes the surface enrichment effect and theoretically how PIXE can be used to study it. It then details the construction of the components of the external-beam setup. Many of the refinements of the hardware and experimental methods are discussed. It recounts the means of calibration of the detector and analytical tools. Finally, an accounting of the research performed on several coins is set forth, along with data showing the effectiveness of PIXE in complementing other methods of elemental analysis. We found that PIXE revealed statistically significant differences in concentrations of modern coins at the two beam energies we used. Ancient coins did not have similarly significant discrepancies between the two beam energies. The modern coin data suggested depletion in copper in copper-silver and copper-gold alloys, which is consistent with predictions of the theory of the surface enrichment effect. We suggest that the ancient coins are so deeply corroded that the PIXE beam is unable to penetrate adequately to observe surface enrichment. Comparison of our PIXE data to XRF and SEM data suggest that the trends we observed in modern coins are verified by the other methods. We therefore assert that external-beam PIXE is an effective tool for studying the surface enrichment effect, though with the beam energies available at Brigham Young University, the study must be limited to fairly modern coins.

<p>Developing radiation delivery systems for optimisation of absorbed dose to the target without normal tissue toxicity requires advanced calculations for transport of radiation. In this thesis absorbed dose and fluence in different radiotherapy applications were calculated by using Monte Carlo (MC) simulations.</p><p>In paper I-III external neutron activation of gadolinium (Gd) for intravascular brachytherapy (GdNCB) and tumour therapy (GdNCT) was investigated. MC codes MCNP and GEANT4 were compared. MCNP was chosen for neutron capture reaction calculations. Gd neutron capture reaction includes both very short range (Auger electrons) and long range (IC electrons and gamma) products. In GdNCB the high-energetic gamma gives an almost flat absorbed dose delivery pattern, up to 4 mm around the stent. Dose distribution at the edges and inside the stent may prevent stent edge and in-stent restenosis. For GdNCT the absorbed dose from prompt gamma will dominate over the dose from IC and Auger electrons in an in vivo situation. The absorbed dose from IC electrons will enhance the total absorbed dose in the tumours and contribute to the cell killing.</p><p>In paper IV a model for calculation of inter-cluster cross-fire radiation dose from β-emitting radionuclides in a breast cancer model was developed. GEANT4 was used for obtaining absorbed dose. The dose internally in cells binding the isotope (self-dose) increased with decreasing β-energy except for the radionuclides with substantial amounts of conversion electrons and Auger electrons. An effective therapy approach may be a combination of radionuclides where the high self-dose from nuclides with low β-energy should be combined with the inter-cell cluster cross-fire dose from high energy β-particles.</p><p>In paper V MC simulations using correlated sampling together with importance sampling were used to calculate spectra perturbations in detector volumes caused by the detector silicon chip and its encapsulation. Penelope and EGSnrc were used and yielded similar results. The low energy part of the electron spectrum increased but to a less extent if the silicon detector was encapsulated in low z-materials.</p>

Developing radiation delivery systems for optimisation of absorbed dose to the target without normal tissue toxicity requires advanced calculations for transport of radiation. In this thesis absorbed dose and fluence in different radiotherapy applications were calculated by using Monte Carlo (MC) simulations. In paper I-III external neutron activation of gadolinium (Gd) for intravascular brachytherapy (GdNCB) and tumour therapy (GdNCT) was investigated. MC codes MCNP and GEANT4 were compared. MCNP was chosen for neutron capture reaction calculations. Gd neutron capture reaction includes both very short range (Auger electrons) and long range (IC electrons and gamma) products. In GdNCB the high-energetic gamma gives an almost flat absorbed dose delivery pattern, up to 4 mm around the stent. Dose distribution at the edges and inside the stent may prevent stent edge and in-stent restenosis. For GdNCT the absorbed dose from prompt gamma will dominate over the dose from IC and Auger electrons in an in vivo situation. The absorbed dose from IC electrons will enhance the total absorbed dose in the tumours and contribute to the cell killing. In paper IV a model for calculation of inter-cluster cross-fire radiation dose from β-emitting radionuclides in a breast cancer model was developed. GEANT4 was used for obtaining absorbed dose. The dose internally in cells binding the isotope (self-dose) increased with decreasing β-energy except for the radionuclides with substantial amounts of conversion electrons and Auger electrons. An effective therapy approach may be a combination of radionuclides where the high self-dose from nuclides with low β-energy should be combined with the inter-cell cluster cross-fire dose from high energy β-particles. In paper V MC simulations using correlated sampling together with importance sampling were used to calculate spectra perturbations in detector volumes caused by the detector silicon chip and its encapsulation. Penelope and EGSnrc were used and yielded similar results. The low energy part of the electron spectrum increased but to a less extent if the silicon detector was encapsulated in low z-materials.

Jamaican males are a high-risk population for aggressive prostate cancer (PrCa) due to genetic influences, and identifying empirical data on treatments, which provide survival benefits is a prime challenge for clinicians who manage Jamaican PrCa patients. Thus, the purpose of this investigation was to elucidate treatment effects of brachytherapy and ERBT in the survival of a Jamaican PrCa cohort. Differences in survival outcomes of brachytherapy and ERBT treated Jamaican, and White U.S.-born PrCa patients with localized PrCa were compared. The mechanism of radiation programmed cell death in PrCa carcinogenesis explained in the oxidative stress theory, was the theoretical base for interpreting the research questions. A retrospective cohort design was used, and included survival analysis of secondary data from the Surveillance Epidemiology and End Results database. The sample size was 10,752 Jamaican and White U.S.-born prostate cancer patients diagnosed between 1992 and 2011. Kaplan-Meier and Cox proportional hazard regression models confirmed that brachytherapy resulted in enhanced survival benefits to the Jamaicans, HR 0.63, 95% CI [0.55, 0.73], p < .001, but ERBT did not, HR 1.6, 95% CI [1.38, 1.84] p < .001. Hence, brachytherapy may be an appropriate treatment option for Jamaican PrCa patients. Clinicians and health care planners can utilize the results for policy decisions aimed at increasing access to brachytherapy treatments to Jamaicans. Improving access to efficient PrCa treatments could reduce the morbidity and mortality rates of PrCa among Jamaicans, decrease years of potential life lost from PrCa, and enhance the life expectancy of the Jamaican male population.

No description available.

This thesis addresses three problems related to image registration, prediction and tracking, applied to Angiography and Oncology. For image analysis, various probabilistic models have been employed to characterize the image deformations, target motions and state estimations. (i) In Digital Subtraction Angiography (DSA), having a high quality visualization of the blood motion in the vessels is essential both in diagnostic and interventional applications. In order to reduce the inherent movement artifacts in DSA, non-rigid image registration is used before subtracting the mask from the contrast image. DSA image registration is a challenging problem, as it requires non-rigid matching across spatially non-uniform control points, at high speed. We model the problem of sub-pixel matching, as a labeling problem on a non-uniform Markov Random Field (MRF). We use quad-trees in a novel way to generate the non uniform grid structure and optimize the registration cost using graph-cuts technique. The MRF formulation produces a smooth displacement field which results in better artifact reduction than with the conventional approach of independently registering the control points. The above approach is further improved using two models. First, we introduce the concept of pivotal and non-pivotal control points. `Pivotal control points' are nodes in the Markov network that are close to the edges in the mask image, while 'non-pivotal control points' are identified in soft tissue regions. This model leads to a novel MRF framework and energy formulation. Next, we propose a Gaussian MRF model and solve the energy minimization problem for sub-pixel DSA registration using Random Walker (RW). An incremental registration approach is developed using quad-tree based MRF structure and RW, wherein the density of control points is hierarchically increased at each level M depending of the features to be used and the required accuracy. A novel numbering scheme of the control points allows us to reuse the computations done at level M in M + 1. Both the models result in an accelerated performance without compromising on the artifact reduction. We have also provided a CUDA based design of the algorithm, and shown performance acceleration on a GPU. We have tested the approach using 25 clinical data sets, and have presented the results of quantitative analysis and clinical assessment. (ii) In External Beam Radiation Therapy (EBRT), in order to monitor the intra fraction motion of thoracic and abdominal tumors, the lung diaphragm apex can be used as an internal marker. However, tracking the position of the apex from image based observations is a challenging problem, as it undergoes both position and shape variation. We propose a novel approach for tracking the ipsilateral hemidiaphragm apex (IHDA) position on CBCT projection images. We model the diaphragm state as a spatiotemporal MRF, and obtain the trace of the apex by solving an energy minimization problem through graph-cuts. We have tested the approach using 15 clinical data sets and found that this approach outperforms the conventional full search method in terms of accuracy. We have provided a GPU based heterogeneous implementation of the algorithm using CUDA to increase the viability of the approach for clinical use. (iii) In an adaptive radiotherapy system, irrespective of the methods used for target observations there is an inherent latency in the beam control as they involve mechanical movement and processing delays. Hence predicting the target position during `beam on target' is essential to increase the control precision. We propose a novel prediction model (called o set sine model) for the breathing pattern. We use IHDA positions (from CBCT images) as measurements and an Unscented Kalman Filter (UKF) for state estimation. The results based on 15 clinical datasets show that, o set sine model outperforms the state of the art LCM model in terms of prediction accuracy.