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Image-guided radiation therapy (IGRT) provides accurate and precise tumour targeting. To ensure adequate coverage in IGRT, a planning target volume (PTV) margin is added around the target to account for treatment uncertainties. Treatment plans are designed to deliver a high percentage of the prescription dose to the PTV; thus, portions of healthy tissue are also subjected to high radiation dose. IGRT employs dedicated devices that enable visual assessment of some treatment uncertainties, such as variations in patient set-up. Safe and effective IGRT delivery requires adherence to disease site-specific protocols that describe process details such as imaging technique, alignment method, and corrective action levels. Protocol design is challenging since its effect on treatment accuracy is currently unknown. This thesis aims to understand the interplay between lung IGRT protocol parameters by developing a framework that quantifies geometrical accuracy. Deformable image registration was used to account for changes in target shape and size throughout treatment. Sufficient accuracy was considered when at least 99% of the target surface fell within the PTV. This analysis revealed that the clinical 10 mm PTV margin can be safely reduced by at least 2 mm in each direction. Evaluation of IGRT accuracy was extended to spinal cord alignment. Simulations were carried out with various matching strategies to correct for set-up error, including rotational off-sets. Inappropriate combinations of matching strategies and safety margins resulted in sub-optimal geometrical coverage. Various lung IGRT protocol options were recommended to optimize accuracy and workflow efficiency. For example, an 8 mm PTV margin can be used with spinal cord alignment, a 4 mm cord margin, and up to 5° of rotational error. A more aggressive protocol involved a 6 mm PTV margin with direct target alignment, a 5 mm cord margin, and a 4° rotational tolerance. / Thesis / Master of Science (MSc)

<p>A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.</p> / Dissertation

An improved method is introduced for prediction of local tumor control following lung stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) patients using 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET). A normalized background-corrected tumor maximum Standard Uptake Value (SUVcmax) is introduced using the mean uptake of adjacent aorta (SUVref), instead of the maximum uptake of lung tumor (SUVmax). This method minimizes the variations associated with SUVmax and objectively demonstrates a strong correlation between the low SUVcmax (< 2.5-3.0) and local control of post lung SBRT. The false positive rates of both SUVmax and SUVcmax increase with inclusion of early (<6 months) PET scans, therefore such inclusion is not recommended for assessing local tumor control of post lung SBRT. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

Intensity Modulated Radiation Therapy (IMRT) is a well-known type of external beam radiation therapy. The advancement in technology has had an inevitable influence in radiation oncology as well that has led to a newer and faster dose delivery technique called Volumetric Modulated Arc Therapy (VMAT). Since the presence of the VMAT modality in clinics in the late 2000, there have been many studies in order to compare the results of the VMAT modality with the current popular modality IMRT for various tumor sites in the body such as brain, prostate, head and neck, cervix and anal carcinoma. This is the first study to compare VMAT with IMRT for breast cancer. The results show that the RapidArc technique in Eclipse version 11 does not improve all aspects of the treatment plans for the breast cases automatically and easily, but it needs to be manipulated by extra techniques to create acceptable plans thus further research is needed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection

<p>Imaging respiratory induced tumor motion in the radiation therapy treatment room could eliminate the necessity for large motion encompassing margins that result in excessive irradiation of healthy tissues. Currently available image guidance technologies are ill-suited for this task. Two-dimensional fluoroscopic images are acquired with sufficient speed to image respiratory motion. However, volume information is not present, and soft tissue structures are often not visible because a large volume is projected onto a single plane. Currently available volumetric imaging modalities are not acquired with sufficient speed to capture full motion trajectory information. Four-dimensional cone-beam computed tomography (4D CBCT) using a gantry mounted 2D flat panel imaging device has been proposed but has been limited by high doses, long scan times and severe under-sampling artifacts. The focus of the work completed in this thesis was to find ways to improve 4D imaging using a gantry mounted 2D kV imaging system. Specifically, the goals were to investigate methods for minimizing imaging dose and scan time while achieving consistent, controllable, high quality 4D images.</p><p>First, we introduced four-dimensional digital tomosynthesis (4D DTS) and characterized its potential for 3D motion analysis using a motion phantom. The motion phantom was programmed to exhibit motion profiles with various known amplitudes in all three dimensions and scanned using a 2D kV imaging system mounted on a linear accelerator. Two arcs of projection data centered about the anterior-posterior and lateral axes were used to reconstruct phase resolved DTS coronal and sagittal images. Respiratory signals were obtained by analyzing projection data, and these signals were used to derive phases for each of the projection images. Projection images were sorted according to phase, and DTS phase images were reconstructed for each phase bin. 4D DTS target location accuracies for peak inhalation and peak exhalation in all three dimensions were limited only by the 0.5 mm pixel resolution for all DTS scan angles. The average localization errors for all phases of an assymetric motion profile with a 2 cm peak-to-peak amplitude were 0.68, 0.67 and 1.85 mm for 60 <super> o <super/> 4D DTS, 360<super> o <super/> CBCT and 4DCT, respectively. Motion artifacts for 4D DTS were found to be substantially less than those seen in 4DCT, which is the current clinical standard in 4D imaging. </p><p>We then developed a comprehensive framework for relating patient respiratory parameters with acquisition and reconstruction parameters for slow gantry rotation 4D DTS and 4D CBCT imaging. This framework was validated and optimized with phantom and lung patient studies. The framework facilitates calculation of optimal frame rates and gantry rotation speeds based on patient specific respiratory parameters and required temporal resolution (task dependent). We also conducted lung patient studies to investigate required scan angles for 4D DTS and achievable dose and scan times for 4D DTS and 4D CBCT using the optimized framework. This explicit and comprehensive framework of relationships allowed us to demonstrate that under-sampling artifacts can be controlled, and 4D CBCT images can be acquired using lower doses than previously reported. We reconstructed 4D CBCT images of three patients with accumulated doses of 4.8 to 5.7 cGy. These doses are three times less than the doses used for the only previously reported 4D CBCT investigation that did not report images characterized by severe under-sampling artifacts. </p><p>We found that scan times for 200<super> o <super/> 4D CBCT imaging using acquisition sequences optimized for reduction of imaging dose and under-sampling artifacts were necessarily between 4 and 7 minutes (depending on patient respiration). The results from lung patient studies concluded that scan times could be reduced using 4D DTS. Patient 4D DTS studies demonstrated that tumor visibility for the lung patients we studied could be achieved using 30<super> o <super/> scan angles for coronal views. Scan times for those cases were between 41 and 50 seconds. Additional dose reductions were also demonstrated. Image doses were between 1.56 and 2.13 cGy. These doses are well below doses for standard CBCT scans. The techniques developed and reported in this thesis demonstrate how respiratory motion can be imaged in the radiotherapy treatment room using clinically feasible imaging doses and scan times.</p> / Dissertation

<p>To date, image localization of mobile tumors prior to radiation delivery has primarily been confined to 2D and 3D technologies, such as fluoroscopy and 3D cone-beam CT (3D-CBCT). Due to the limited information from these images, larger volumes of healthy tissue are often irradiated in order to ensure the radiation field encompasses the entirety of the target motion. Since the overarching goal of radiation therapy is to deliver maximum dose to cancerous cells and simultaneously minimize the radiation delivered to healthy surrounding tissues, it would be ideal to use 4D imaging to obtain time-resolved volume images of the tumor motion during respiration. </p><p>4D-CBCT imaging has been previously investigated, but has not yet seen large clinical translation due to the obstacles of long acquisition time and large image radiation dose. Furthermore, 4D-CBCT currently requires the use of external surrogates to correlate the patient's respiration with the image acquisition process. This correlation has been under question by a multitude of studies demonstrating the uncertainties that exist between the surrogate and the actual motion of the internal anatomy. Errors in the correlation process may result in image artifacts, which could potentially lead to reconstructions with inaccurate target volumes, thereby defeating the purpose of even using 4D-CBCT. </p><p>It is therefore the aim of this dissertation to initially highlight an additional limitation of using 3D-CBCT for imaging respiratory motion and thereby reiterate the need for 4D-CBCT imaging in the treatment room, develop a simple and efficient technique to achieve markerless, self-sorted 4D-CBCT and finally to comprehensively evaluate its robustness across a variety of potential clinical scenarios with a digital human phantom. </p><p>People often spend a longer period of time exhaling as compared with inhaling, and some do so in an extremely disproportionate manner. To demonstrate the disadvantage of using 3D-CBCT in such instances, a dynamic thorax phantom was imaged with a large variety of simulated and patient-derived respiratory traces of ratios of time spent in the inspiration phase versus time spent in the expiration phase (I/E ratio). Canny edge detection and contrast measures were employed to compare the internal target volumes (ITVs) generated per profile. The results revealed that an I/E ratio of less than one can lead to potential underestimation of the ITV with the severity increasing as the inspiration becomes more disproportionate to the expiration. This occurs because of the loss of contrast in the inspiration phase, due to the fewer number of projections acquired there. The measured contrast reduction was as high as 94% for small targets (0.5 cm) moving large amplitudes (2.0 cm) and still as much as 22.3% for large targets (3.0 cm) moving small amplitudes (0.5 cm). This is alarming because the degraded visibility of the target in the inspiration phase may inaccurately impact the alignment of the planning ITV with that of the FB-CBCT and thereby affect the accuracy of the localization and consequent radiation delivery. These potential errors can be avoided with the use of 4D-CBCT instead, to form the composite volume and serve as the verification ITV for alignment.</p><p>In order to delineate accurate target volumes from 4D-CBCT phase images, it is crucial that the projections be properly associated with the patient's respiration. Thus, in order to improve previously developed 4D-CBCT techniques, the basics of Fourier Transform (FT) theory were utilized to extract the respiratory signal directly from the acquired projection data. Markerless, self-sorted 4D-CBCT reconstruction was achieved by developing methods based on the phase and magnitude information of the Fourier Transform. Their performance was subsequently compared to the gold standard of visual identification of peak-inspiration projections. Slow-gantry acquired projections of two sets of physical phantom data with sinusoidal respiratory cycles of 3 and 6 seconds as well as three patients were used as initial evaluation of the feasibility of the Fourier technique. Quantitative criteria consisted of average difference in respiratory phase (ADRP) and percentage of projections assigned within 10% respiratory phase of the gold standard (PP10). For all five projection datasets, the results supported feasibility of both FT-Phase and FT-Magnitude methods with ADRP values less than 5.3% and PP10 values of 87.3% and above. </p><p>Because the technique proved to be promising in the initial feasibility study, a more comprehensive evaluation was necessary in order to assess the robustness of the technique across a larger set of possibilities that may be encountered in the clinic. A 4D digital XCAT phantom was used to generate an array of respiratory and anatomical variables that affect the performance of the technique. The respiratory variables studied included: inspiration to expiration ratio, respiratory cycle length, diaphragmatic motion amplitude, AP chest wall expansion amplitude, breathing irregularities such as baseline shift and inconsistent peak-inspiration amplitude, as well as six breathing profiles derived from cine-MRI images of three healthy volunteers and three lung cancer patients. The anatomical variables studied included: male and female patient size (physical dimension and adipose content), body-mass-index (BMI) category, tumor location, and percentage of the lung in the field-of-view (FOV) of the projection data. CBCT projections of each XCAT phantom were then generated. Additional external imaging factors such as image noise and detector wobble were added to select cases with different percentages of lung in the projection FOV to investigate any effects on the robustness. FT-Phase and FT-Magnitude were each applied and quantitatively compared to the gold standard. Both methods proved to be robust across the studied scenarios with ADRP<10% and PP10>90%, when incorporating minor modifications to region-of-interest (ROI) selection and/or low-frequency location to certain cases of diaphragm amplitude and lung percentage in the FOV of the projection (for which a method may have previously struggled). Nevertheless, in the instance where one method initially faltered, the other method prevailed and successfully identified peak-inspiration projections. This is promising because it suggests that the two methods provide complementary information to each other. To ensure appropriate clinical adaptation of markerless, self-sorted 4D-CBCT, perhaps an optimal integration of the two methods can be developed.</p> / Dissertation

Prostate cancer is the most common type of cancer afflicting Canadian men. Image-guided external radiation therapy of prostate cancer requires the accurate positioning of the patient in the treatment field. The alignment process is done using three fiducial markers implanted in the prostate. The current clinical practice involves the manual localization of these markers on pre-treatment, low-resolution electronic portal images (EPI). We propose an algorithm for the automatic detection of these markers. Our approach first enhances the quality of the EPI images using a fully automatic image enhancement approach. Next, fiducial markers are detected using template matching and a novel way of integrating information across multiple views. Experimental results show a significant improvement in the detection of fiducial markers in the left lateral view with respect to state-of-the-art results in related work. One should note that the left lateral view is the most challenging view due to the low resolution and the presence of occluding bony structures. / Graduate

Thesis (M. Sc.)--University of Canterbury, 2008. / Typescript (photocopy). "Year 2006-2008"--P. i. Includes bibliographical references (p. 122-123). Also available via the World Wide Web.

<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