<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>

A prerequisite for modern radiotherapy is the ability to accurately determine the absorbed dose (D) that is given to the patient. The subject of this thesis has been to develop and evaluate efficient dose calculation models for high-energy photon beams delivered by linear accelerators. Even though the considered calculation models are general, the work has been focused on quality assurance (QA) tools used to independently verify the dose for individual treatment plans. The purpose of this verification is to guarantee patient safety and to improve the treatment outcome. Furthermore, a vital part of this work has been to explore the prospect of estimating the dose calculation uncertainties associated with individual treatment setups. A discussion on how such uncertainty estimations can facilitate improved clinical QA procedures by providing appropriate action levels has also been included within the scope of this thesis. In order to enable efficient modelling of the physical phenomena that are involved in dose output calculations it is convenient to divide them into two main categories; the first one dealing with the radiation exiting the accelerator’s treatment head and a second one associated with the subsequent energy deposition processes. A multi-source model describing the distribution of energy fluence emitted from the treatment head per delivered monitor unit (MU) is presented and evaluated through comparisons with measurements in multiple photon beams and collimator settings. The calculations show close agreement with the extensive set of experimental data, generally within +/-1% of corresponding measurements. The energy (dose) deposition in the irradiated object has been modelled through a photon pencil kernel solely based on a beam quality index (TPR20,10). This model was evaluated in a similar manner as the multi-source model at three different treatment depths. A separate study was focused on the specific difficulties associated with dose calculations in points located at a distance from the central beam axis. Despite the minimal input data required to characterize individual photon beams, the accuracy proved to be very good when comparing the calculated results with experimental data. The evaluated calculation models were finally used to analyse how well the lateral dose distributions from typical megavoltage photon beams are optimized with respect to the resulting beam flatness characteristics. The results did not reveal any obvious reasons why different manufacturers should provide different lateral dose distributions. Furthermore, the performed lateral optimizations indicate that there is room for improved flatness performance for the investigated linear accelerators.

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. 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. 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.

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. 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. 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>The online adaptive radiation therapy for prostate cancer based on re-optimization has been shown to provide better daily target coverage through the treatment course, especially in treatment sessions with large anatomical deformation. However, the clinical implementation of such technique is still limited primarily due to two major challenges: the low efficiency of re-optimization and the lack of online quality assurance technique to verify delivery accuracy. This project aims at developing new techniques and understandings to address these two challenges. </p><p>The study was based on retrospective study on patient data following IRB-approved protocol, including both planning Computer Tomography (CT) and daily Cone-Beam Computer Tomography (CBCT) images. The project is divided in to three parts. The first two parts address primarily the efficiency challenge; and the third part of this project aims at validating the deliverability of the online re-optimized plans and developing an online delivery monitoring system. </p><p><bold>I. Overall implementation scheme.</bold> In this part, an evidence-based scheme, named Adaptive Image-Guided Radiation Therapy (AIGRT), was developed to integrate the re-optimization technique with the current IGRT technique. The AIGRT process first searches for a best plan for the daily target from a plan pool, which consists the original CT plan and all previous re-optimized plans. If successful, the selected plan is used for the daily treatment with translational shifts. Otherwise, the AIGRT invokes re-optimization process of the CT plan for the anatomy-of-the-day, which is added to the plan pool afterwards as a candidate plan for future fractions. The AIGRT scheme is evaluated by comparisons with daily re-optimization and online repositioning techniques based on daily target coverage, Organ-at-Risk (OAR) sparing and implementation efficiency. Simulated treatment courses for 18 patients with re-optimization alone, re-positioning alone and AIGRT shows that AIGRT offers reliable daily target coverage that is highly comparable to re-optimization everyday and significantly improves compared to re-positioning. AIGRT is also seen to provide improved organs-at-risk (OARs) sparing compared to re-positioning. Apart from dosimetric benefits, AIGRT in addition offers an efficient scheme to integrate re-optimization to current re-positioning-based IGRT workflow.</p><p><bold>II. Strategies for automatic re-optimization.</bold> This part aims at improving the efficiency of re-optimization through automation and strategic selections of optimization parameters. It investigates the strategies for performing fast (~2 min) automatic online re-optimization with a clinical treatment planning system; and explores the performance with different input parameters settings: the DVH objective settings, starting stage and iteration number (in the context of real time planning). Simulated treatments of 10 patients were re-optimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting re-optimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analysed by statistical modelling, and compared both in terms of dosimetry and delivery efficiency. The results show that all fast online re-optimized plans provide consistent coverage and conformity to the daily target. For OAR sparing however, different planning parameters led to different optimization results. The 3 input parameters, i.e. DVH objectives, starting stages and iteration numbers, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the original plan fluence map as the starting stage reduced OAR dose at the mid-dose region, but increased 17% more monitor units. Only < 2cc differences in OAR V50% / V70Gy / V76Gy were observed between 100 and 50 iterations. Based on these results, it is feasible to perform automatic online re-optimization in ~2 min using a clinical treatment planning system. Selecting optimal sets of input parameters is the key to achieving high quality re-optimized plans, and should be based on the individual patient's daily anatomy, delivery efficiency and time allowed for plan adaptation. </p><p><bold>III. Delivery accuracy evaluation and monitoring.</bold> This part of the project aims at validating the deliverability of the online re-optimized plans and developing an online delivery monitoring system. This system is based on input from Dynamic Machine Information (DMI), which continuously reports actual multi-leaf collimator (MLC) positions and machine monitor units (MUs) at 50ms intervals. Based on these DMI inputs, the QA system performed three levels of monitoring/verification on the plan delivery process: (1) Following each input, actual and expected fluence maps delivered up to the current MLC position were dynamically updated using corresponding MLC positions in the DMI. The difference between actual and expected fluence maps creates a fluence error map (FEM), which is used to assess the delivery accuracy. (2) At each control point, actual MLC positions were verified against the treatment plan for potential errors in data transfer between the treatment planning system (TPS) and the MLC controller. (3) After treatment, delivered dose was reconstructed in the treatment planning system based on DMI data during delivery, and compared to planned dose. FEMs from 210 prostate IMRT beams were evaluated for error magnitude and patterns. In addition, systematic MLC errors of ±0.5 and ±1 mm for both banks were simulated to understand error patterns in resulted FEMs. Applying clinical IMRT QA standard to the online re-optimized plans suggests the deliverability of online re-optimized plans are similar to regular IMRT plans. Applying the proposed QA system to online re-optimized plans also reveals excellent delivery accuracy: over 99% leaf position differences are < 0.5 mm, and the majority of pixels in FEMs are < 0.5 MU with errors exceeding 0.5 MU primarily located on the edge of the fields. All clinical FEMs observed in this study have positive errors on the left edges, and negative errors on the right. Analysis on a typical FEM reveals positive correlation between the magnitude of fluence errors and the corresponding leaf speed. FEMs of simulated erroneous delivery exhibit distinct patterns for different MLC error magnitudes and directions, indicating the proposed QA system is highly specific in detecting the source of errors. Based on these results, it can be concluded that the proposed online delivery monitoring system is very sensitive to leaf position errors, highly specific of the error types, and therefore meets the purpose for online delivery accuracy verification. Post-treatment dosimetric verification shows minimal difference between planned and actual delivered DVH, further confirming that the online re-optimized plans can be accurately delivered.</p><p>In summary, this project addressed two most important challenges for clinical implementation of online ART, efficiency and quality assurance, through innovative system design, technique development and validation with clinical data. The efficiencies of the overall treatment scheme and the re-optimization process have been improved significantly; and the proposed online quality assurance system is found to be effective in catching and differentiating leaf motion errors.</p> / Dissertation

<p>The use of positron emission tomography (PET) in radiation therapy has continued to grow, especially since the development of combined computed tomography (CT) and PET imaging system in the early 1990s. Today, the biggest use of PET-CT is in oncology, where a glucose analog radiotracer is rapidly incorporated into the metabolic pathways of a variety of cancers. Images representing the in-vivo distribution of this radiotracer are used for the staging, delineation and assessment of treatment response of patients undergoing chemotherapy or radiation therapy. While PET offers the ability to provide functional information, the imaging quality of PET is adversely affected by its lower spatial resolution. It also has unfavorable image noise characteristics due to radiation dose concerns and patient compliance. These factors result in PET images having less detail and lower signal-to-noise (SNR) properties compared to images produced by CT. This complicates the use of PET within many areas of radiation oncology, but particularly the delineation of targets for radiation therapy and the assessment of patient response to therapy. The development of segmentation methods that can provide accurate object identification in PET images under a variety of imaging conditions has been a goal of the imaging community for years. The goal of this thesis are to: (1) investigate the effect of filtering on segmentation methods; (2) investigate whether combining individual segmentation methods can improve segmentation accuracy; (3) investigate whether the consensus volumes can be useful in aiding physicians of different experience in defining gross tumor volumes (GTV) for head-and-neck cancer patients; and (4) to investigate whether consensus volumes can be useful in assessing early treatment response in head-and-neck cancer patients.</p><p>For this dissertation work, standard spherical objects of volumes ranging from 1.15 cc to 37 cc and two irregularly shaped objects of volume 16 cc and 32 cc formed by deforming high density plastic bottles were placed in a standardized image quality phantom and imaged at two contrasts (4:1 or 8:1 for spheres, and 4.5:1 and 9:1 for irregular) and three scan durations (1, 2 and 5 minutes). For the work carried out into the comparison of images filters, Gaussian and bilateral filters matched to produce similar image signal to noise (SNR) in background regions were applied to raw unfiltered images. Objects were segmented using thresholding at 40% of the maximum intensity within a region-of-interest (ROI), an adaptive thresholding method which accounts for the signal of the object as well as background, k-means clustering, and a seeded region-growing method adapted from the literature. Quality of the segmentations was assessed using the Dice Similarity Coefficient (DSC) and symmetric mean absolute surface distance (SMASD). Further, models describing how DSC varies with object size, contrast, scan duration, filter choice and segmentation method were fitted using generalized estimating equations (GEEs) and standard regression for comparison. GEEs accounted for the bounded, correlated and heteroscedastic nature of the DSC metric. Our analysis revealed that object size had the largest effect on DSC for spheres, followed by contrast and scan duration. In addition, compared to filtering images with a 5 mm full-width at half maximum (FWHM) Gaussian filter, a 7 mm bilateral filter with moderate pre-smoothing (3 mm Gaussian (G3B7)) produced significant improvements in 3 out of the 4 segmentation methods for spheres. For the irregular objects, time had the biggest effect on DSC values, followed by contrast. </p><p>For the study of applying consensus methods to PET segmentation, an additional gradient based method was included into the collection individual segmentation methods used for the filtering study. Objects in images acquired for 5 minute scan durations were filtered with a 5 mm FWHM Gaussian before being segmented by all individual methods. Two approaches of creating a volume reflecting the agreement between the individual methods were investigated. First, a simple majority voting scheme (MJV), where individual voxels segmented by three or more of the individual methods are included in the consensus volume, and second, the Simultaneous Truth and Performance Level Estimation (STAPLE) method which is a maximum likelihood methodology previously presented in the literature but never applied to PET segmentation. Improvements in accuracy to match or exceed the best performing individual method were observed, and importantly, both consensus methods provided robustness against poorly performing individual methods. In fact, the distributions of DSC and SMASD values for the MJV and STAPLE closely match the distribution that would result if the best individual method result were selected for all objects (the best individual method varies by objects). Given that the best individual method is dependent on object type, size, contrast, and image noise and the best individual method is not able to be known before segmentation, consensus methods offer a marked improvement over the current standard of using just one of the individual segmentation methods used in this dissertation. </p><p>To explore the potential application of consensus volumes to radiation therapy, the MJV consensus method was used to produce GTVs in a population of head and neck cancer patients. This GTV and one created using simple 40% thresholding were then available to be used as a guidance volume for an attending head and neck radiation oncologist and a resident who had completed their head and neck rotation. The task for each physician was to manually delineate GTVs using the CT and PET images. Each patient was contoured three times by each physician- without guidance and with guidance using either the MJV consensus volume or 40% thresholding. Differences in GTV volumes between physicians were not significant, nor were differences between the GTV volumes regardless of the guidance volume available to the physicians. However, on average, 15-20% of the provided guidance volume lay outside the final physician-defined contour.</p><p>In the final study, the MJV and STAPLE consensus volumes were used to extract maximum, peak and mean SUV measurements in two baseline PET scans and one PET scan taken during patients' prescribed radiation therapy treatments. Mean SUV values derived from consensus volumes showed smaller variability compared to maximum SUV values. Baseline and intratreatment variability was assessed using a Bland-Altman analysis which showed that baseline variability in SUV was lower than intratreatment changes in SUV.</p><p>The techniques developed and reported in this thesis demonstrate how filter choice affects segmentation accuracy, how the use of GEEs more appropriately account for the properties of a common segmentation quality metric, and how consensus volumes not only provide an accuracy on par with the single best performing individual method in a given activity distribution, but also exhibit a robustness against variable performance of individual segmentation methods that make up the consensus volume. These properties make the use of consensus volumes appealing for a variety of tasks in radiation oncology.</p> / Dissertation

Geometric errors may compromise the quality of radiation therapy treatments. Optimization methods that account for errors can reduce their effects. The first paper of this thesis introduces minimax optimization to account for systematic range and setup errors in intensity-modulated proton therapy. The minimax method optimizes the worst case outcome of the errors within a given set. It is applied to three patient cases and shown to yield improved target coverage robustness and healthy structure sparing compared to conventional methods using margins, uniform beam doses, and density override. Information about the uncertainties enables the optimization to counterbalance the effects of errors. In the second paper, random setup errors of uncertain distribution---in addition to the systematic range and setup errors---are considered in a framework that enables scaling between expected value and minimax optimization. Experiments on a phantom show that the best and mean case tradeoffs between target coverage and critical structure sparing are similar between the methods of the framework, but that the worst case tradeoff improves with conservativeness. Minimax optimization only considers the worst case errors. When the planning criteria cannot be fulfilled for all errors, this may have an adverse effect on the plan quality. The third paper introduces a method for such cases that modifies the set of considered errors to maximize the probability of satisfying the planning criteria. For two cases treated with intensity-modulated photon and proton therapy, the method increased the number of satisfied criteria substantially. Grasping for a little less sometimes yields better plans. In the fourth paper, the theory for multicriteria optimization is extended to incorporate minimax optimization. Minimax optimization is shown to better exploit spatial information than objective-wise worst case optimization, which has previously been used for robust multicriteria optimization. The fifth and sixth papers introduce methods for improving treatment plans: one for deliverable Pareto surface navigation, which improves upon the Pareto set representations of previous methods; and one that minimizes healthy structure doses while constraining the doses of all structures not to deteriorate compared to a reference plan, thereby improving upon plans that have been reached with too weak planning goals. / <p>QC 20130516</p>

<p>Digital tomosynthesis (DTS) is a quasi-three-dimensional (3D) imaging technique which reconstructs images from a limited angle of cone-beam projections with shorter acquisition time, lower imaging dose, and less mechanical constraint than full cone-beam CT (CBCT). However, DTS images reconstructed by the conventional filtered back projection method have low plane-to-plane resolution, and they do not provide full volumetric information for target localization due to the limited angle of the DTS acquisition. </p><p>This dissertation presents the optimization and clinical implementation of image guided radiation therapy using limited-angle projections.</p><p>A hybrid multiresolution rigid-body registration technique was developed to automatically register reference DTS images with on-board DTS images to guide patient positioning in radiation therapy. This hybrid registration technique uses a faster but less accurate static method to achieve an initial registration, followed by a slower but more accurate adaptive method to fine tune the registration. A multiresolution scheme is employed in the registration to further improve the registration accuracy, robustness and efficiency. Normalized mutual information is selected as the criterion for the similarity measure, and the downhill simplex method is used as the search engine. This technique was tested using image data both from an anthropomorphic chest phantom and from head-and-neck cancer patients. The effects of the scan angle and the region-of-interest size on the registration accuracy and robustness were investigated. The average capture ranges in single-axis simulations with a 44° scan angle and a large ROI covering the entire DTS volume were between -31 and +34 deg for rotations and between -89 and +78 mm for translations in the phantom study, and between -38 and +38 deg for rotations and between -58 and +65 mm for translations in the patient study.</p><p>Additionally, a novel limited-angle CBCT estimation method using a deformation field map was developed to optimally estimate volumetric information of organ deformation for soft tissue alignment in image guided radiation therapy. The deformation field map is solved by using prior information, a deformation model, and new projection data. Patients' previous CBCT data are used as the prior information, and the new patient volume to be estimated is considered as a deformation of the prior patient volume. The deformation field is solved by minimizing bending energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. The new patient CBCT volume is then obtained by deforming the prior patient CBCT volume according to the solution to the deformation field. The method was tested for different scan angles in 2D and 3D cases using simulated and real projections of a Shepp-Logan phantom, liver, prostate and head-and-neck patient data. Hardware acceleration and multiresolution scheme are used to accelerate the 3D estimation process. The accuracy of the estimation was evaluated by comparing organ volume, similarity and pixel value differences between limited-angle CBCT and full-rotation CBCT images. Results showed that the respiratory motion in the liver patient, rectum volume change in the prostate patient, and the weight loss and airway volume change in the head-and-neck patient were accurately estimated in the 60° CBCT images. This new estimation method is able to optimally estimate the volumetric information using 60-degree projection images. It is both technically and clinically feasible for image-guidance in radiation therapy.</p> / Dissertation

The objectives of this research were to test treatment and survival differences between women and men with lung cancer as there is minimal investigation in the literature. Three research questions were developed with statistical testing for gender differences based on similar cancer type, stage, treatment assignment and survival. Data for 44,863 primary lung cancer cases were collected from eight U.S. state-based cancer registries to investigate the research questions. The lung cancer incidence data included the morphological cell-types of adenocarcinoma (AC); squamous cell carcinoma (SCC); large cell carcinoma (LCC) and small cell carcinoma (SCC). Stage, grade, treatment type, as well as, individual characteristics such as gender, age at diagnosis, marital status at diagnosis and race were other variables obtained to be included in the statistical models. Reporting the overall effect for lung cancer gender specific treatment differences or survival has not been demonstrated in the literature to the author's knowledge. By convention, main effects and interaction effects are reported in the literature; without including an evaluation the overall effect of a variable on the outcome, possible misinterpretations could be made. For example, utilizing the Cox's Proportional Hazards model when the interaction effect of gender and treatment type received was examined, females were at an increased risk for death by as much 29% as compared to males (HR = 1.18, 95% CI 1.09 - 1.29). But when the gender effect on survival was assessed, there was an increase in females survivorship as compared to males by as much as 28% (HR = 0.80, 95% CI 0.72 - 0.97 ). In conclusion, by using a unique statistical approach, statistically significant Odds Ratios and Hazard Ratios were demonstrated for the research data set when the overall interaction effect on the outcome was examined. Recommendations to health care practitioners include adhering to current guidelines, e.g. American Medical Association, for lung cancer treatments. Standard treatment protocols were not always followed for early stage disease, e.g. females versus males with stage I lung cancer were 1.71 times more likely to receive chemotherapy in combination with radiation therapy versus a standard first treatment course of surgery (OR = 1.71, 95% CI 1.06 - 2.78). Also, depending on the lung cancer morphology and lung cancer treatment, females as compared to males could exhibit an increase in survivorship by as much as 28%. To improve the results of medical care decisions for lung cancer, clinicians may find the information presented in this study useful and encourage further research on which treatment increases survival for both men and women.

<p>A bench-top dual cone-beam computed tomography (CBCT) system was developed consisting of two orthogonally placed 40x30 cm<super>2</super> flat-panel detectors and two conventional X-ray tubes with two individual high-voltage generators sharing the same rotational axis. The X-ray source to detector distance is 150 cm and X-ray source to rotational axis distance is 100 cm for both subsystems. The objects are scanned through 200° of rotation. The dual CBCT (DCBCT) system utilized 110° of projection data from one detector and 90° from the other while the two individual single CBCTs utilized 200° data from each detector. The system performance was characterized in terms of uniformity, contrast, spatial resolution, noise power spectrum and CT number linearity. The uniformity, within the axial slice and along the longitudinal direction, and noise power spectrum were assessed by scanning a water bucket; the contrast and CT number linearity were measured using the Catphan phantom; and the spatial resolution was evaluated using a tungsten wire phantom. A skull phantom and a ham were also scanned to provide qualitative evaluation of high- and low-contrast resolution. Each measurement was compared between dual and single CBCT systems.</p><p>Compared with single CBCT, the DCBCT presented: 1) a decrease in uniformity by 1.9% in axial view and 1.1% in the longitudinal view, as averaged for four energies (80, 100, 125 and 150 kVp); 2) comparable or slightly better contrast to noise ratio (CNR) for low-contrast objects and comparable contrast for high-contrast objects; 3) comparable spatial resolution; 4) comparable CT number linearity with R<super>2</super> &#8805; 0.99 for all four tested energies; 5) lower noise power spectrum in magnitude. DCBCT images of the skull phantom and the ham demonstrated both high-contrast resolution and good soft-tissue contrast.</p><p>One of the major challenges for clinical implementation of four-dimensional (4D) CBCT is the long scan time. To investigate the 4D imaging capabilities of the DCBCT system, motion phantom studies were conducted to validate the efficiency by comparing 4D images generated from 4D-DCBCT and 4D-CBCT. First, a simple sinusoidal profile was used to confirm the scan time reduction. Next, both irregular sinusoidal and patient-derived profiles were used to investigate the advantage of temporally correlated orthogonal projections due to a reduced scan time. Normalized mutual information (NMI) between 4D-DCBCT and 4D-CBCT was used for quantitative evaluation.</p><p>For the simple sinusoidal profile, the average NMI for ten phases between two single 4D-CBCTs was 0.336, indicating the maximum NMI that can be achieved for this study. The average NMIs between 4D-DCBCT and each single 4D-CBCT were 0.331 and 0.320. For both irregular sinusoidal and patient-derived profiles, 4D-DCBCT generated phase images with less motion blurring when compared with single 4D-CBCT.</p><p>For dual kV energy imaging, we acquired 80kVp projections and 150 kVp projections, with an additional 0.8 mm tin filtration. The virtual monochromatic (VM) technique was implemented, by first decomposing these projections into acrylic and aluminum basis material projections to synthesize VM projections, which were then used to reconstruct VM CBCTs. The effect of the VM CBCT on metal artifact reduction was evaluated with an in-house titanium-BB phantom. The optimal VM energy to maximize CNR for iodine contrast and minimize beam hardening in VM CBCT was determined using a water phantom containing two iodine concentrations. The linearly-mixed (LM) technique was implemented by linearly combining the low- (80kVp) and high-energy (150kVp) CBCTs. The dose partitioning between low- and high-energy CBCTs was varied (20%, 40%, 60% and 80% for low-energy) while keeping total dose approximately equal to single-energy CBCTs, measured using an ion chamber. Noise levels and CNRs for four tissue types were investigated for dual-energy LM CBCTs in comparison with single-energy CBCTs at 80, 100, 125 and 150kVp.</p><p>The VM technique showed a substantial reduction of metal artifacts at 100 keV with a 40% reduction in the background standard deviation compared with a 125 kVp single-energy scan of equal dose. The VM energy to maximize CNR for both iodine concentrations and minimize beam hardening in the metal-free object was 50 keV and 60 keV, respectively. The difference in average noise levels measured in the phantom background was 1.2% for dual-energy LM CBCTs and equivalent-dose single-energy CBCTs. CNR values in the LM CBCTs of any dose partitioning were better than those of 150 kVp single-energy CBCTs. The average CNRs for four tissue types with 80% dose fraction at low-energy showed 9.0% and 4.1% improvement relative to 100 kVp and 125 kVp single-energy CBCTs, respectively. CNRs for low contrast objects improved as dose partitioning was more heavily weighted towards low-energy (80kVp) for LM CBCTs.</p><p>For application of the dual-energy technique in the kilovoltage (kV) and megavoltage (MV) range, we acquired both MV projections (from gantry angle of 0° to 100°) and kV projections (90° to 200°) with the current orthogonal kV/MV imaging hardware equipped in modern linear accelerators, as gantry rotated a total of 110°. A selected range of overlap projections between 90° to 100° were then decomposed into two material projections using experimentally determined parameters from orthogonally stacked aluminum and acrylic step-wedges. Given attenuation coefficients of aluminum and acrylic at a predetermined energy, one set of VM projections could be synthesized from two corresponding sets of decomposed projections. Two linear functions were generated using projection information at overlap angles to convert kV and MV projections at non-overlap angles to approximate VM projections for CBCT reconstruction. The CNRs were calculated for different inserts in VM CBCTs of a CatPhan phantom with various selected energies and compared with those in kV and MV CBCTs. The effect of overlap projection number on CNR was evaluated. Additionally, the effect of beam orientation was studied by scanning the CatPhan sandwiched with two 5 cm solid-water phantoms on both lateral sides and an electronic density phantom with two metal bolt inserts.</p><p>Proper selection of VM energy (30keV and 40keV for low-density polyethylene (LDPE), polymethylpentene (PMP), 2MeV for Delrin) provided comparable or even better CNR results as compared with kV or MV CBCT. An increased number of overlap between kV and MV projections demonstrated only marginal improvements of CNR for different inserts (with the exception of LDPE) and therefore one projection overlap was found to be sufficient for the CatPhan study. It was also evident that the optimal CBCT image quality was achieved when MV beams penetrated through the heavy attenuation direction of the object. </p><p>In conclusion, the performance of a bench-top DCBCT imaging system has been characterized and is comparable to that of a single CBCT. The 4D-DCBCT provides an efficient 4D imaging technique for motion management. The scan time is reduced by approximately a factor of two. The temporally correlated orthogonal projections improved the image blur across 4D phase images. Dual-energy CBCT imaging techniques were implemented to synthesize VM CBCT and LM CBCTs. VM CBCT was effective at achieving metal artifact reduction. Depending on the dose-partitioning scheme, LM CBCT demonstrated the potential to improve CNR for low contrast objects compared with single-energy CBCT acquired with equivalent dose. A novel technique was developed to generate VM CBCTs from kV/MV projections. This technique has the potential to improve CNR at selected VM energies and to suppress artifacts at appropriate beam orientations.</p> / Dissertation