Dans le contexte du traitement du cancer de la prostate, l’utilisation de la tomodensitométrie à faisceau conique (CBCT) pour la radiothérapie guidée par l’image, éventuellement adaptative, présente certaines difficultés en raison du faible contraste et du bruit important dans les images pelviennes. L’objectif principal de cette thèse est d’apporter des contributions méthodologiques pour le recalage automatique entre l’image scanner CT de référence et l’image CBCT acquise le jour du traitement. La première partie de nos contributions concerne le développement d’une stratégie de correction du positionnement du patient à l’aide du recalage rigide (RR) CT/CBCT. Nous avons comparé plusieurs algorithmes entre eux : (a) RR osseux, (b) RR osseux suivi d’un RR local dans une région qui correspond au clinical target volume (CTV) de la prostate dans l’image CT élargie d’une marge allant de 1 à 20 mm. Une analyse statistique complète des résultats quantitatifs et qualitatifs utilisant toute la base de données, composée de 115 images cone beam computed tomography (CBCT) et de 10 images computed tomography (CT) de 10 patients atteints du cancer de la prostate, a été réalisée. Nous avons également défini une nouvelle méthode pratique et automatique pour estimer la distension rectale produite dans le voisinage de la prostate entre l’image CT et l’image CBCT. A l’aide de notre mesure de distension rectale, nous avons évalué l’impact de la distension rectale sur la qualité du RR local et nous avons fourni un moyen de prédire les échecs de recalage. Sur cette base, nous avons élaboré des recommandations concernant l’utilisation du RR automatique pour la localisation de la prostate sur les images CBCT en pratique clinique. La seconde partie de la thèse concerne le développement méthodologique d’une nouvelle méthode combinant le recalage déformable et la segmentation. Pour contourner le problème du faible rapport qualité/bruit dans les images CBCT qui peut induire le processus de recalage en erreur, nous avons imaginé une nouvelle énergie composée de deux termes : un terme de similarité globale (la corrélation croisée normalisée (NCC) a été utilisée, mais tout autre mesure de similarité pourrait être utilisée à la place) et un terme de segmentation qui repose sur une adaptation locale du modèle de l’image homogène par morceaux de Chan-Vese utilisant un contour actif dans l’image CBCT. Notre but principal était d’améliorer la précision du recalage comparé à une énergie constituée de la NCC seule. Notre algorithme de recalage est complètement automatique et accepte comme entrées (1) l’image CT de planification, (2) l’image CBCT du jour et (3) l’image binaire associée à l’image CT et correspondant à l’organe d’intérêt que l’on cherche à segmenter dans l’image CBCT au cours du recalage. / The use of CBCT imaging for image-guided radiation therapy (IGRT), and beyond that, image-guided adaptive radiation therapy (IGART), in the context of prostate cancer is challenging due to the poor contrast and high noise in pelvic CBCT images. The principal aim of the thesis is to provide methodological contributions for automatic intra-patient image registration between the planning CT scan and the treatment CBCT scan. The first part of our contributions concerns the development of a CBCT-based prostate setup correction strategy using CT-to-CBCT rigid registration (RR). We established a comparison between different RR algorithms: (a) global RR, (b) bony RR, and (c) bony RR refined by a local RR using the prostate CTV in the CT scan expanded with 1- to-20-mm varying margins. A comprehensive statistical analysis of the quantitative and qualitative results was carried out using the whole dataset composed of 115 daily CBCT scans and 10 planning CT scans from 10 prostate cancer patients. We also defined a novel practical method to automatically estimate rectal distension occurred in the vicinity of the prostate between the CT and the CBCT scans. Using our measure of rectal distension, we evaluated the impact of rectal distension on the quality of local RR and we provided a way to predict registration failure. On this basis, we derived recommendations for clinical practice for the use of automatic RR for prostate localization on CBCT scans. The second part of the thesis provides a methodological development of a new joint segmentation and deformable registration framework. To deal with the poor contrast-to-noise ratio in CBCT images likely to misguide registration, we conceived a new metric (or enery) which included two terms: a global similarity term (the normalized cross correlation (NCC) was used, but any other one could be used instead) and a segmentation term based on a localized adaptation of the piecewise-constant region-based model of Chan-Vese using an evolving contour in the CBCT image. Our principal aim was to improve the accuracy of the registration compared with an ordinary NCC metric. Our registration algorithm is fully automatic and takes as inputs (1) the planning CT image, (2) the daily CBCT image and (3) the binary image associated with the CT image and corresponding to the organ of interest we want to segment in the CBCT image in the course of the registration process.

<p>The developments of highly conformal and precise radiation therapy techniques promote the necessity of more accurate treatment target localization and tracking. On-board imaging techniques, especially the x-ray based techniques, have found a great popularity nowadays for on-board target localization and tracking. With an objective to improve the accuracy of on-board imaging for lung cancer patients, the dissertation work focuses on the investigations of using limited-angle on-board x-ray projections for image guidance. The limited-angle acquisition enables scan time and imaging dose reduction and improves the mechanical clearance of imaging.</p><p>First of all, the dissertation developed a phase-matched digital tomosynthesis (DTS) technique using limited-angle (<=30 deg) projections for lung tumor localization. This technique acquires the same traditional motion-blurred on-board DTS image as the 3D-DTS technique, but uses the planning 4D computed tomography (CT) to synthesize a phase-matched reference DTS to register with the on-board DTS for tumor localization. Of the 324 different scenarios simulated using the extended cardiac torso (XCAT) digital phantom, the phase-matched DTS technique localizes the 3D target position with an localization error of 1.07 mm (± 0.57 mm) (average ± standard deviation (S.D.)). Similarly, for the total 60 scenarios evaluated using the computerized imaging reference system (CIRS) 008A physical phantom, the phase-matched DTS technique localizes the 3D target position with an average localization error of 1.24 mm (± 0.87 mm). In addition to the phantom studies, preliminary clinical cases were also studied using imaging data from three lung cancer patients. Using the localization results of 4D cone beam computed tomography (CBCT) as `gold-standard', the phase-matched DTS techniques localized the tumor to an average localization error of 1.5 mm (± 0.5 mm). </p><p>The phantom and patient study results show that the phase-matched DTS technique substantially improved the accuracy of moving lung target localization, as compared to the 3D-DTS technique. The phase-matched DTS technique can provide accurate lung target localizations like 4D-DTS, but with much reduced imaging dose and scan time. The phase-matched DTS technique is also found more robust, being minimally affected by variations of respiratory cycle lengths, fractions of respiration cycle contained within the DTS scan and the scan directions, which potentially enables quasi-instantaneous (within a sub-breathing cycle) moving target verification during radiation therapy, preferably arc therapy.</p><p>Though the phase-matched DTS technique can provide accurate target localization under normal scenarios, its accuracy is limited when the patient on-board breathing experiences large variations in motion amplitudes. In addition, the limited-angle based acquisition leads to severe structural distortions in DTS images reconstructed by the current clinical gold-standard Feldkamp-Davis-Kress (FDK) reconstruction algorithm, which prohibit accurate target deformation tracking, delineation and dose calculation. </p><p>To solve the above issues, the dissertation further developed a prior knowledge based image estimation technique to fundamentally change the landscape of limited-angle based imaging. The developed motion modeling and free-form deformation (MM-FD) method estimates high quality on-board 4D-CBCT images through applying deformation field maps to existing prior planning 4D-CT images. The deformation field maps are solved using two steps: first, a principal component analysis based motion model is built using the planning 4D-CT (motion modeling). The deformation field map is constructed as an optimized linear combination of the extracted motion modes. Second, with the coarse deformation field maps obtained from motion modeling, a further fine-tuning process called free-form deformation is applied to further correct the residual errors from motion modeling. Using the XCAT phantom, a lung patient with a 30 mm diameter tumor was simulated to have various anatomical and respirational variations from the planning 4D-CT to on-board 4D-CBCTs, including respiration amplitude variations, tumor size variations, tumor average position variations, and phase shift between tumor and body respiratory cycles. The tumors were contoured in both the estimated and the `ground-truth' on-board 4D-CBCTs for comparison. 3D volume percentage error (VPE) and center-of-mass error (COME) were calculated to evaluate the estimation accuracy of the MM-FD technique. For all simulated patient scenarios, the average (± S.D.) VPE / COME of the tumor in the prior image without image estimation was 136.11% (± 42.76%) / 15.5 mm (± 3.9 mm). Using orthogonal-view 30 deg scan angle, the average VPE/COME of the tumors in the MM-FD estimated on-board images was substantially reduced to 5.22% (± 2.12%) / 0.5 mm (± 0.4 mm). </p><p>In addition to XCAT simulation, CIRS phantom measurements and actual patient studies were also performed. For these clinical studies, we used the normalized cross-correlation (NCC) as a new similarity metric and developed an updated MMFD-NCC method, to improve the robustness of the image estimation technique to the intensity mismatches between CT and CBCT imaging systems. Using 4D-CBCT reconstructed from fully-sampled on-board projections as `gold-standard', for the CIRS phantom study, the average (± S.D.) VPE / COME of the tumor in the prior image and the tumors in the MMFD-NCC estimated images was 257.1% (± 60.2%) / 10.1 mm (± 4.5 mm) and 7.7% (± 1.2%) / 1.2 mm (± 0.2mm), respectively. For three patient cases, the average (± S.D.) VPE / COME of tumors in the prior images and tumors in the MMFD-NCC estimated images was 55.6% (± 45.9%) / 3.8 mm (± 1.9 mm) and 9.6% (± 6.1%) / 1.1 mm (± 0.5 mm), respectively. With the combined benefits of motion modeling and free-form deformation, the MMFD-NCC method has achieved highly accurate image estimation under different scenarios. </p><p>Another potential benefit of on-board 4D-CBCT imaging is the on-board dose calculation and verification. Since the MMFD-NCC estimates the on-board 4D-CBCT through deforming prior 4D-CT images, the 4D-CBCT inherently has the same image quality and Hounsfield unit (HU) accuracy as 4D-CT and therefore can potentially improve the accuracy of on-board dose verification. Both XCAT and CIRS phantom studies were performed for the dosimetric study. Various inter-fractional variations featuring patient motion pattern change, tumor size change and tumor average position change were simulated from planning CT to on-board images. The doses calculated on the on-board CBCTs estimated by MMFD-NCC (MMFD-NCC doses) were compared to the doses calculated on the `gold-standard' on-board images (gold-standard doses). The absolute deviations of minimum dose (DDmin), maximum dose (DDmax), mean dose (DDmean) and prescription dose coverage (DV100%) of the planning target volume (PTV) were evaluated. In addition, 4D on-board treatment dose accumulations were performed using 4D-CBCT images estimated by MMFD-NCC in the CIRS phantom study. The accumulated doses were compared to those measured using optically stimulated luminescence (OSL) detectors and radiochromic films. </p><p>The MMFD-NCC doses matched very well with the gold-standard doses. For the XCAT phantom study, the average (± S.D.) DDmin, DDmax, DDmean and DV100% (values normalized by the prescription dose or the total PTV volume) between the MMFD-NCC PTV doses and the gold-standard PTV doses were 0.3% (± 0.2%), 0.9% (± 0.6%), 0.6% (± 0.4%) and 1.0% (± 0.8%), respectively. Similarly, for the CIRS phantom study, the corresponding values between the MMFD-NCC PTV doses and the gold-standard PTV doses were 0.4% (± 0.8%), 0.8% (± 1.0%), 0.5% (± 0.4%) and 0.8% (± 0.8%), respectively. For the 4D dose accumulation study, the average (± S.D.) absolute dose deviation (normalized by local doses) between the accumulated doses and the OSL measured doses was 3.0% (± 2.4%). The average gamma index (3%/3mm) between the accumulated doses and the radiochromic film measured doses was 96.1%. The MMFD-NCC estimated 4D-CBCT enables accurate on-board dose calculation and accumulation for lung radiation therapy under different scenarios. It can potentially be valuable for treatment quality assessment and adaptive radiation therapy.</p><p>However, a major limitation of the estimated 4D-CBCTs above is that they can only capture inter-fractional patient variations as they were acquired prior to each treatment. The intra-treatment patient variations cannot be captured, which can also affect the treatment accuracy. In light of this issue, an aggregated kilo-voltage (kV) and mega-voltage (MV) imaging scheme was developed to enable intra-treatment imaging. Through using the simultaneously acquired kV and MV projections during the treatment, the MMFD-NCC method enabled 4D-CBCT estimation using combined kV and MV projections. </p><p>For all XCAT-simulated patient scenarios, the average (± S.D.) VPE / COME of the tumor in the prior image and tumors in the MMFD-NCC estimated images (using kV + open field MV) was 136.11% (± 42.76%) / 15.5 mm (± 3.9 mm) and 4.5% (± 1.9%) / 0.3 mm (± 0.4 mm), respectively. In contrast, the MMFD-NCC estimation using kV + beam's eye view (BEV) MV projections yielded results of 4.3% (± 1.5%) / 0.3 mm (± 0.3 mm). The kV + BEV MV aggregation can estimate the target as accurately as the kV + open field MV aggregation. The impact of this study is threefold: 1. the kV and MV projections can be acquired at the same time. The imaging time will be cut to half as compared to the cases which use kV projections only. 2. The kV and MV aggregation enables intra-treatment imaging and target tracking, since the MV projections can be the side products of the treatment beams (BEV MV). 3. As the BEV MV projections originate from the treatment beams, there will be no extra MV imaging dose to the patient.</p><p>The above introduced 4D-CBCT estimation techniques were all based on limited-angle acquisition. Though limited-angle acquisition enables substantial scan time and dose reduction as compared to the full-angle scan, it is still not real-time and cannot provide `cine' imaging, which refers to the instantaneous imaging with negligible scan time and imaging dose. Cine imaging is important in image guided radiation therapy practice, considering the respirational variations may occur quickly and frequently during the treatment. For instance, the patient may experience a breathing baseline shift after every respiratory cycle. The limited-angle 4D-CBCT approach still requires a scan time of multiple respiratory cycles, which will not be able to capture the baseline shift in a timely manner. </p><p>In light of this issue, based on the previously developed MMFD-NCC method, an AI-FD-NCC method was further developed to enable quasi-cine CBCT imaging using extremely limited-angle (<=6 deg) projections. Using pre-treatment 4D-CBCTs acquired just before the treatment as prior information, AI-FD-NCC enforces an additional prior adaptive constraint to estimate high quality `quasi-cine' CBCT images. Two on-board patient scenarios: tumor baseline shift and continuous motion amplitude change were simulated through the XCAT phantom. Using orthogonal-view 6 deg projections, for the baseline shift scenario, the average (± S.D.) VPE / COME of the tumors in the AI-FD-NCC estimated images was 1.3% (± 0.5%) / 0.4 mm (± 0.1 mm). For the amplitude variation scenario, the average (± S.D.) VPE / COME of the tumors in the AI-FD-NCC estimated images was 1.9% (± 1.1%) / 0.5 mm (± 0.2 mm). The impact of this study is three-fold: first, the quasi-cine CBCT technique enables actual real-time volumetric tracking of tumor and normal tissues. Second, the method enables real-time tumor and normal tissues dose calculation and accumulation. Third, the high-quality volumetric images obtained can potentially be used for real-time adaptive radiation therapy.</p><p>In summary, the dissertation work uses limited-angle on-board x-ray projections to reconstruct/estimate volumetric images for lung tumor localization, delineation and dose calculation. Limited-angle acquisition reduces imaging dose, scan time and improves imaging mechanical clearance. Using limited-angle projections enables continuous, sub respiratory-cycle tumor localization, as validated in the phase-matched DTS study. The combination of prior information, motion modeling, free-form deformation and limited-angle on-board projections enables high-quality on-board 4D-CBCT estimation, as validated by the MM-FD / MMFD-NCC techniques. The high-quality 4D-CBCT not only can be applied for accurate target localization and delineation, but also can be used for accurate treatment dose verification, as validated in the dosimetric study. Through aggregating the kV and MV projections for image estimation, intra-treatment 4D-CBCT imaging was also proposed and validated for its feasibility. At last, the introduction of more accurate prior information and additional adaptive prior knowledge constraints also enables quasi-cine CBCT imaging using extremely-limited angle projections. The dissertation work contributes to lung on-board imaging in many aspects with various approaches, which can be beneficial to the future lung image guided radiation therapy practice.</p> / Dissertation

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 goal of this study was to improve dosimetry for pelvic, lung, head and neck, and other cancers sites with aspherical planning target volumes (PTV) using a new algorithm for collimator optimization for intensity modulated radiation therapy (IMRT) that minimizes the x-jaw gap (CAX) and the area of the jaws (CAA) for each treatment field. A retroactive study on the effects of collimator optimization of 20 patients was performed by comparing metric results for new collimator optimization techniques in Eclipse version 11.0. Keeping all other parameters equal, multiple plans are created using four collimator techniques: CA0, all fields have collimators set to 0°, CAE, using the Eclipse collimator optimization, CAA, minimizing the area of the jaws around the PTV, and CAX, minimizing the x-jaw gap. The minimum area and the minimum x-jaw angles are found by evaluating each field beam’s eye view of the PTV with ImageJ and finding the desired parameters with a custom script. The evaluation of the plans included the monitor units (MU), the maximum dose of the plan, the maximum dose to organs at risk (OAR), the conformity index (CI) and the number of fields that are calculated to split. Compared to the CA0 plans, the monitor units decreased on average by 6% for the CAX method with a p-value of 0.01 from an ANOVA test. The average maximum dose remained within 1.1% difference between all four methods with the lowest given by CAX. The maximum dose to the most at risk organ was best spared by the CAA method, which decreased by 0.62% compared to the CA0. Minimizing the x-jaws significantly reduced the number of split fields from 61 to 37. In every metric tested the CAX optimization produced comparable or superior results compared to the other three techniques. For aspherical PTVs, CAX on average reduced the number of split fields, lowered the maximum dose, minimized the dose to the surrounding OAR, and decreased the monitor units. This is achieved while maintaining the same control of the PTV. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Evaluation of dose optimization using the Pencil Beam (PB) and Monte Carlo (MC) algorithms may allow physicists to apply dosimetric offsets to account for inaccuracies of the PB algorithm for lung cancer treatment with Stereotactic Body Radiotherapy (SBRT). 20 cases of Non-Small Cell Lung Cancer (NSCLC) were selected. Treatment plans were created with Brainlab iPlanDose® 4.1.2. The D97 of the Planning Target Volume (PTV) was normalized to 50 Gy on the Average Intensity Projection (AIP) using the fast PB and compared with MC. This exact plan with the same beam Monitor Units (MUs) was recalculated over each respiratory phase. The results show that the PB algorithm has a 2.3-2.4% less overestimation at the maximum exhalation phase than the maximum inhalation phase when compared to MC. Significantly smaller dose difference between PB and MC is also shown in plans for peripheral lesions (7.7 ± 0.7%) versus central lesions (12.7±0.8%)(p< 0.01). / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

The purpose of this research is to accurately match the calculation environment, i.e. the treatment planning system (TPS) with the measurement environment (using a 2-D diode array) for lung Stereotactic Body Radiation Therapy (SBRT) patient-specific quality assurance (QA). Furthermore, a new phantom was studied in which the 2-D array and heterogeneities were incorporated into the patient-specific QA process for lung SBRT. Dual source dual energy computerized tomography (DSCT) and single energy computerized tomography (SECT) were used to model phantoms incorporating a 2-D diode array into the TPS. A water-equivalent and a heterogeneous phantom (simulating the thoracic region of a patient) were studied. Monte Carlo and pencil beam dose distributions were compared to the measured distributions. Composite and individual fields were analyzed for normally incident and planned gantry angle deliveries. The distributions were compared using γ-analysis for criteria 3% 3mm, 2% 2mm, and 1% 1mm. The Monte Carlo calculations for the DSCT modeled phantoms (incorporating the array) showed an increase in the passing percentage magnitude for 46.4 % of the fields at 3% 3mm, 85.7% at 2% 2mm, and 92.9% at 1% 1mm. The Monte Carlo calculations gave no agreement for the same γ-analysis criteria using the SECT. Pencil beam calculations resulted in lower passing percentages when the diode array was incorporated in the TPS. The DSCT modeled phantoms (incorporating the array) exhibited decrease in the passing percentage magnitude for 85.7% of the fields at 3% 3mm, 82.1% at 2% 2mm, and 71.4% at 1% 1mm. In SECT modeled phantoms (incorporating the array), a decrease in passing percentage magnitude were found for 92.9% of the fields at 3% 3mm, 89.3% at 2% 2mm, and 82.1% at 1% 1mm. In conclusion, this study demonstrates that including the diode array in the TPS results in increased passing percentages when using a DSCT system with a Monte Carlo algorithm for patient-specific lung SBRT QA. Furthermore, as recommended by task groups (e.g. TG 65, TG 101, TG 244) of the American Association of Physicists in Medicine (AAPM), pencil beam algorithms should be avoided in the presence of heterogeneous materials, including a diode array. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

Considerando as dificuldades que ocorrem com a localização e o posicionamento de implantes e, ainda, o risco de deslocamento das guias, tomográfica e cirúrgica, durante os procedimentos de diagnóstico e cirúrgico, foi objetivo desta pesquisa avaliar, se a alternativa de introduzir dispositivos para retenção e suporte, nas guias da técnica de cirurgia guiada convencional, interfere na posição e inclinação de implantes no momento da sua colocação. Foram confeccionados 10 modelos simulando tecido ósseo, divididos aleatoriamente em 2 grupos: 5 com a guia tomográfica e cirúrgica da técnica convencional, denominado grupo controle (M); 5 com as guias fixadas a ortoimplantes modificados associados ao sistema de encaixe o ring, representando o grupo experimental (MI). A avaliação dos resultados foi pela sobreposição dos planejamentos virtuais (Implant Viewer), derivados de tomografias computadorizadas pré-cirúrgicas, com as realizadas após a colocação dos implantes. Os resultados obtidos mostraram que não houve diferenças estatisticamente significantes para os desvios angulares (Teste Tukey F= 1,06 e p= 0, 3124) e lineares (Teste ANOVA F = 2,54 e p = 0,11). No entanto, os valores angulares individuais do grupo experimental (MI), mostraram ser mais próximos entre si, com menor variabilidade, quando comparados ao grupo controle. Concluiuse, que o uso de ortoimplantes associados ao sistema de encaixe o ring, pode trazer benefícios à técnica da cirurgia guiada convencional, reduzindo as alterações de posicionamento dos implantes no momento da sua colocação. / Computer guided surgery is an excellent alternative to the proper insertion of implants in patients with an edentulous arch or a partially edentulous area and with appropriate quantity of bone. Considering the difficulties that occur with implants placement and the risk of displacement of radiographic and surgical template during the diagnostic and surgical procedures, the aim of this research was to assess if an alternative devices for retention of radiographic and surgical templates can bring benefits for a more accurate implant placement. Ten models made by a material that simulates bone tissue were randomly divided into 2 groups: 5 with the conventional radiographic and surgical guide, which was called control group (M); 5 with modified orthodontic implants that fixed the radiographic and the surgical templates, representing the experimental group (MI). The evaluation of the results was by matching virtual plans (Implant Viewer), derived from pre-operative cone-beam CT images, with post-operative ones to calculate the deviation between planned and installed implants. The results showed that there was no statistically significant differences for angular (Tukey F = 1.06 and p = 0, 3124) and linear deviations (test ANOVA F = 2.54 and p = 0.11). However, the individual angular values of experimental group (MI) showed to be closer to each other, with lower variability when compared to control group. It was concluded that the use of modified orthodontic implant with o ring attachment can bring benefits to conventional guided surgery technique, reducing changes in ideal implant position.

Empirical methods of beam angle optimization (BAO) are tested against the BAO that is currently employed in Eclipse treatment planning software. Creating an improved BAO can decrease the amount of time a dosimetrist spends on making a treatment plan, improve the treatment quality and enhance the tools an inexperienced dosimetrist can use to develop planning techniques. Using empirical data created by experienced dosimetrists from 69 patients treated for lung cancer, the most frequently used gantry angles were applied to four different regions in each lung to gather an optimal set of fields that could be used to treat future lung cancer patients. This method, given the moniker FAU BAO, is compared in 7 plans created with the Eclipse BAO choosing 5 fields and 9 fields. The results show that the conformality index improved by 30% or 3% when using the 5 and 9 fields. The conformation number was better by 12% from the 5 fields and 9% from the 9 fields. The organs at risk (OAR) were overall more protected to produce fewer nonstochastic effects from the radiation treatment with the FAU BAO. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

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