Intensity modulated radiation therapy (IMRT) is a cancer treatment method in which the intensities of the radiation beams are modulated; therefore these beams have non-uniform radiation intensities. The overall result is the delivery of the prescribed dose in the target volume. The dose distribution is conformal to the shape of the target and minimizes the dose to the nearby critical organs. An inverse planning algorithm is used to obtain those non-uniform beam intensities. In inverse treatment planning, the treatment plan is achieved by using an optimization process. The optimized plan results to a high-quality dose distribution in the planning target volume (PTV), which receives the prescribed dose while the dose that is received by the organs at risk (OARs) is reduced. Accordingly, an objective function has to be defined for the PTV, while some constraints have to be considered to handle the dose limitations for the OARs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

The purpose of this research is to determine the feasibility of introducing the Monte Carlo (MC) dose calculation algorithm into the clinical practice. Unlike the Ray Tracing (RT) algorithm, the MC algorithm is not affected by the tissue inhomogeneities, which are significant inside the chest cavity. A retrospective study was completed for 102 plans calculated using both the RT and MC algorithms. The D95 of the PTV was 26% lower for the MC calculation. The first parameter of conformality, as defined as the ratio of the Prescription Isodose Volume to the PTV Volume was on average 1.27 for RT and 0.67 for MC. The results confirm that the RT algorithm significantly overestimates the dosages delivered confirming previous analyses. Correlations indicate that these overestimates are largest for small PTV and/or when the ratio of the volume of lung tissue to the PTV approaches 1. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Cirurgia conservadora de mama seguida de radioterapia é considerada como tratamento padrão para câncer de mama. A radioterapia intraoperatória (IORT) pode ser vantajosa, pois diminui o tempo de tratamento, geralmente de 4 a 6 semanas, para uma única fração, aplicada durante o procedimento cirúrgico. As distribuições de doses para tratamento por IORT não são bem conhecidas, pois o volume a ser irradiado é definido no momento da aplicação e não existe uma rotina de otimização do plano. Dessa forma as distribuições de dose não foram foco de estudos até o momento, de forma que torna-se interessante conhece-las. O objetivo do presente trabalho é simular e comparar as distribuições de doses para IORT com diferentes feixes e geometrias mamárias e compará-las com as distribuições obtidas para radioterapia 3D (3DR). Através do pacote de simulação Monte Carlo PENELOPE foram obtidas as distribuições de doses em técnicas radioterápicas 3DR e IORT por feixe de elétrons, gerados pelo acelerador NOVAC7, e por raios-X de baixa energia, gerado pelo acelerador Intrabeam. A validação dos feixes estudados, realizada através de comparação com dados da literatura, mostrou, para o feixe de 3DR, o perfil de dose esperado para os feixes com os filtros simulados. As maiores diferenças ocorreram nas regiões de horns, que aparecem subestimados na simulação. Para os feixes de IORT, as maiores diferenças entre simulação e literatura, de 7,79 e 8,6 pontos percentuais, respectivamente para NOVAC7 e Intrabeam, ocorrem em baixas profundidades. A simulação do tratamento para três diferentes volumes mamários gerou distribuições de doses que puderam ser usadas para comparação qualitativa entre as técnicas de tratamento. Para 3DR, as distribuições de doses mostram que parte considerável da dose é depositada no tórax. Embora as maiores doses sejam entregues dentro do volume da mama, ocorrem regiões frias dentro desse volume. As distribuições de dose obtidas para o Intrabeam mostraram que parte da dose pode ser entregue no tórax, dependendo do volume mamário e da posição do aplicador. O tratamento com NOVAC7 apresentou distribuições mais homogêneas dentro do volume alvo, em relação às outras técnicas. De forma geral, os resultados indicam que os tratamentos podem ser largamente influenciados pelo tamanho e posicionamento do campo para 3DR e posicionamento do aplicador para ambas as técnicas de IORT. O tratamento através do Intrabeam é comparável à 3DR. Segundo os parâmetros de avaliação do plano, IORT por feixe de elétrons proporcionaria o melhor tratamento, independentemente do volume mamário. / Conservative breast surgery followed by radiation therapy is considered the standart treatment for breast cancer. Intraoperative radiation therapy (IORT) has the advantage of decreasing the treatment duration, from the usual 4 to 6 weeks, to a single fraction, delivered during the surgical procedure. The dose distribution for treatment given through IORT are not well known, as the volume to be irradiated is defined at the moment of treatment deliver and there is not a plan optimization routine. Therefore the dose distributions were not, to the moment, the goal of any study, what makes interesting to know them. The goal of the present work is to simulate and compare the IORT dose distribution for different beams and breast geometries, and to compare to the 3D radiation therapy (3DR) dose distribution. The dose distributions for 3DR and for electron beam IORT, generated by the NOVAC7 dedicated accelerator, and for low energy x-ray IORT, generated by Intrabeam dedicated accelerator, were obtained using the Monte Carlo simulation package PENELOPE. The beams validation, performed through comparison with literature data, showed, for the 3DR beam, the dose profile expected for the simulated filters. The greatest differences occurred at the horns region, that appear sub estimated in the simulation. For IORT beams the greatest difference between simulation and literature, of 7.79 and 8.6 percentage points, respectively for the NOVAC7 and Intrabeam, occurred at low depths. The treatment simulation, with three different breast volumes, generated dose distributions that were used for a qualitative comparison of the techniques. 3DR dose distribution showed that a considerable fraction of the dose was delivered to the thorax. Although the highest doses were delivered inside the breast volume, cold regions occurred inside this volume also. Intrabeam dose distributions showed that part of the dose may be delivered to the thorax, given the breast volume and applicator position. The treatment through NOVAC7 presented more homogeneous dose distribution in relation to the other techniques. In general the results indicated that the treatment may be greatly affected by field size and position in 3DR and by the applicator position for both of the IORT techniques. Treatment through low energy x-ray IORT is comparable to 3DR treatment. According to the plan evaluation parameters electron beam IORT could give the best treatment for all the breast volumes evaluated.

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.

Motivated by the need to standardize preclinical imaging for image-guided radiation therapy (IGRT), we examine the parameters that influence microcomputed tomography (microCT) scans in the realm of image quality and absorbed dose to tissue, including therapy beam measurements of small fields. Preclinical radiation research aims to understand radiation-induced effects in living tissues to improve quality of life. Small targets and low kilovoltage x-rays create challenges that do not arise in clinical radiation therapy. Evidence based on our multi-institutional study reveals a considerable aberration in microCT image quality from one institution to the next. We propose the adoption of recommended tolerance levels to provide a baseline for producing satisfactory and reproducible microCT image quality scans for accurate dose delivery in preclinical IGRT. Absorbed dose imparted by these microCT images may produce deterministic effects that can negatively influence a radiobiological study. Through Monte Carlo (MC) methods we establish absorbed microCT imaging dose to a variety of tissues and murine sizes for a comprehensive combination of imaging parameters. Radiation beam quality in the small confines of a preclinical irradiator is also established to quantify the effects of beam scatter on half-value layer measurements. MicroCT scans of varying imaging protocols are also compared for murine subjects. Absorbed imaging dose to tissues are established and presented alongside their respective microCT images, providing a visual bridge to systematically link image quality and imaging dose. We then characterize a novel small plastic scintillating dosimeter to experimentally measure microCT imaging and therapy beams in real-time. The presented scintillating dosimeter is specifically characterized for the low energies and small fields found in preclinical research. Beam output is measured for small fields previously only achievable using film. Finally, quality assurance tests are recommended for a preclinical IGRT unit. Within this dissertation, a narrative is presented for guiding preclinical radiotherapy towards producing high quality microCT images with an understanding of the absorbed imaging dose deposited to tissues, including providing a tool to measure small radiation fields. / Graduate

Poor completion rates in the radiation therapy associate's degree program offered through a community college did not meet the standards set by the college and damaged the program's reputation. The relationship between admission criteria and program completion was not known. The purpose of this study was to determine if there were any relationships between the admission criteria (GPA in prerequisite courses, interview scores, writing sample scores, and preadmission testing scores) and students' completion of a radiation therapy associate's degree program. This correlational study used 2 stages of Tinto's retention theory: (a) recruitment and admission to college and (b) pre-entry assessment and placement. Retrospective data, collected from an accredited radiation therapy program offering a 2-year degree, provided a sample size of 70 anonymous student records. The point biserial coefficient was used to analyze the data. The results yielded a significant, moderate, positive relationship between the interview score and student completion. No other significant relationships were found. The professional development program that was derived from the study sought to teach program directors about interview skills and tactics. The ability to identify at-risk students in the admission process is expected to contribute to social change by improving completion rates; improving satisfaction among students, faculty, employers; and ultimately improving the quality of patient care.

The thesis aims to improve treatment dose accuracy in brachytherapy using a high dose rate (HDR) Ir-192 stepping source and in external beam therapy using intensity modulated radiation therapy (IMRT). For HDR brachytherapy, this has been achieved by investigating dose errors in the near field and the transit dose of the HDR brachytherapy stepping source. For IMRT, this study investigates the volume effect of detectors in the dosimetry of small fields, and the clinical implementation and dosimetric verification of a 6MV photon beam for IMRT. For the study of dose errors in the near field of an HDR brachytherapy stepping source, the dose rate at point P at 0.25 cm in water from the transverse bisector of a straight catheter was calculated with Monte Carlo code MCNP 4.A. The Monte Carlo (MC) results were used to compare with the results calculated with the Nucletron Brachytherapy Planning System (BPS) formalism. Using the MC calculated radial dose function and anisotropy function with the BPS formalism, 1% dose calculation accuracy can be achieved even in the near field with negligible extra demand on computation time. A video method was used to analyse the entrance, exit and the inter-dwell transit speed of the HDR stepping source for different path lengths and step sizes ranging from 2.5 mm to 995 mm. The transit speeds were found to be ranging from 54 to 467 mm/s. The results also show that the manufacturer has attempted to compensate for the effects of inter-dwell transit dose by reducing the actual dwell time of the source. A well-type chamber was used to determine the transit doses. Most of the measured dose differences between stationary and stationary plus inter-dwell source movement were within 2%. The small-field dosimetry study investigates the effect of detector size in the dosimetry of small fields and steep dose gradients with a particular emphasis on IMRT measurements. Due to the finite size of the detector, local discrepancies of more than 10 % are found between calculated cross profiles of intensity modulated beams and intensity modulated profiles measured with film. A method to correct for the spatial response of finite sized detectors and to obtain the

The chief aim in developing radiation treatment plans is to maximise tumour cell kill while minimising the killing of normal cells. The acceptance by a radiation oncologist of a radiation therapy treatment plan devised by the radiation therapist, at present is largely based on the oncologists' previous clinical experience with reference to established patterns of treatment and their clinical interpretation of the dose volume histogram. Some versions of radiotherapy planning computer software now incorporate a function that permits biologically based predictions about the probability of tumour control (TCP) and/or normal tissue complications (NTCP). The biological models used for these probabilities are founded upon statistical and mathematical principles as well as radiobiology concepts. TCP and NTCP potentially offer the capability of being able to better optimise treatments for an individual patient's tumour and normal anatomy. There have been few attempts in the past to correlate NTCPs to actual treatment complications, and the reported complications have generally not shown any significant correlation. Thus determining whether either or both NTCPs and TCPs could be correlated with the observed clinical outcomes of prostate radiotherapy is the central topic of this thesis. In this research, TCPs and NTCPs were prospectively calculated for prostate cancer patients receiving radiation therapy, and subsequently assessed against the clinical results of the delivered treatments. This research was conducted using two different types of NTCP models, which were correlated against observed treatment-induced complications in the rectum and bladder. The two NTCP models were also compared to determine their relative efficacy in predicting the recorded toxicities. As part of this research the refinement of some of the published bladder parameters required for NTCP calculations was undertaken to provide a better fit between predicted and observed complication rates for the bladder wall which was used in this research. TCPs were also calculated for each patient using the best available estimate of the radiosensitivity of the prostate gland from recent research. The TCP/NTCP data was analysed to determine if any correlations existed between the calculated probabilities and the observed clinical data. The results of the analyses showed that a correlation between the NTCP and a limited number of toxicities did occur. Additionally the NTCP predictions were compared to existing parameters and methods for radiotherapy plan evaluation - most notably DVHs. It is shown that NTCPs can provide superior discriminatory power when utilised for prospective plan evaluation. While the TCP could not be correlated with clinical outcomes due to insufficient follow-up data, it is shown that there was a correlation between the TCP and the treatment technique used.

<p>In this thesis, a model of tissue oxygenation is presented, that takes into account the heterogeneous nature of tumor vasculature. Even though the model is rather simple, the resulting oxygen distributions agree very well with clinically observed oxygen distributions for most tumors and healthy normal tissues. The model shows that the vascular density may not describe the oxygenation of a tissue sufficiently well, unless the heterogeneity of the vascular system is taken into account. Based on the oxygen distributions from the tissue model, the associated radiation response at low and high doses can be determined. </p><p>The radiation response of heterogeneous tumors should preferably be described by two clonogen compartments, one resistant and one sensitive, dominating the response at high and low radiation doses, respectively. Furthermore, each compartment should be characterized by the effective radiation resistance and the effective clonogen number. The resistant-sensitive model of radiation response has been analyzed in great detail. It accurately describes the response of severely heterogeneous tumors, both at low and high doses and LET values. The effective response parameters are given as integrals, averaged over the whole spectrum of radiation resistance. The parameters can also be determined from clinically established dose-response relations. </p><p>The main properties of the dose-response relation for a generally heterogeneous tumor is described in some detail. The normalized dose-response gradient has been generalized to take heterogeneities in both dose delivery and radiation response into account. This quantity is important for accurate treatment plan optimization using intensity modulated radiation therapy for individual patients. </p>

<p>The main objective of radiation therapy is to obtain the highest possible probability of tumor cure while minimizing adverse reactions in healthy tissues. A crucial step in the treatment process is to determine the location and extent of the primary tumor and its loco regional lymphatic spread in relation to adjacent radiosensitive anatomical structures and organs at risk. These volumes must also be accurately delineated with respect to external anatomic reference points, preferably on surrounding bony structures. At the same time, it is essential to have the best possible physical and radiobiological knowledge about the radiation responsiveness of the target tissues and organs at risk in order to achieve a more accurate optimization of the treatment outcome.</p><p>A computerized whole body Atlas has therefore been developed to serve as a dynamic database, with systematically integrated knowledge, comprising all necessary physical and radiobiological information about common target volumes and normal tissues. The Atlas also contains a database of segmented organs and a lymph node topography, which was based on the Visible Human dataset, to form standard reference geometry of organ systems. The reference knowledgebase and the standard organ dataset can be utilized for Atlas-based image processing and analysis in radiation therapy planning and for biological optimization of the treatment outcome. Atlas-based segmentation procedures were utilized to transform the reference organ dataset of the Atlas into the geometry of individual patients. The anatomic organs and target volumes of the database can be converted by elastic transformation into those of the individual patient for final treatment planning. Furthermore, a database of reference treatment plans was started by implementing state-of-the-art biologically based radiation therapy planning techniques such as conformal, intensity modulated, and radiobiologically optimized treatment planning.</p><p>The computerized Atlas can be viewed as a central framework that contains different forms of optimal treatment plans linked to all the essential information needed in treatment planning, which can be adapted to a given patient, in order to speed up treatment plan convergence. The Atlas also offers a platform to synthesize the results of imaging studies through its advanced geometric transformation and segmentation procedures. The whole body Atlas is anticipated to become a physical and biological knowledgebase that can facilitate, speed up and increase the accuracy in radiation therapy planning and treatment optimization.</p>