DEVELOPMENT OF A ROBUST TREATMENT DELIVERY FRAMEWORK FOR STEREOTACTIC BODY RADIOTHERAPY (SBRT) OF SYNCHRONOUS MULTIPLE LUNG LESIONS

Stereotactic body radiation therapy (SBRT) of lung tumors uses high doses of radiation to deliver high biological effective doses (BED) in very few fractions (1-5). With the use of highly conformal fields to cover the tumor without depositing large doses to non-cancerous structures, this technique has proven time and again to be successful at achieving high local control. However, frequently patients receiving SBRT are elderly with multiple medical comorbidities who may not tolerate long treatment times. Furthermore, many patients present with oligometastatic or multiple primary lung tumors. The success of SBRT on oligometastatic lung disease relies on physician experience with precise patient positioning and immobilization, not available in all clinics. Likewise, there is no standard framework to guide radiation oncology clinics experienced in SBRT with planning and treating multiple lung tumors synchronously. This dissertation explores the treatment planning methods available for the SBRT of multiple lung lesions and presents innovative solutions to the challenges in current practice. To begin, two treatment planning methods for multiple lesion SBRT are compared: treating each lesion individually with separate isocenters and treating all lesions at the same time with a single isocenter. Treating multiple lesions with multiple isocenters will increase the patient’s imaging and treatment time and the number of instances a radiation therapist must enter the treatment room, thus increasing the chances a patient will move from the setup position. Using an individual isocenter placed between the tumors and volumetric arc therapy (VMAT) to treat all tumors at the same time can reduce the treatment time, increasing patient comfort and decreasing the chance of movement from the treatment position. However, there is a chance of decreased target coverage and reduced BED due to small setup errors in the SBRT of synchronous lesions using a single-isocenter. The dissertation continues by quantifying this loss in target coverage using a novel simulation method. Simulations yielded average deviations of 27.4% (up to 72% loss) (p \u3c 0.001) from planned target coverage. The largest deviations from planned coverage and desired BED were seen for the smallest targets (\u3c 10 cc), some of which received \u3c 100 Gy BED, which is suboptimal for SBRT. Patient misalignment resulted in a substantial decrease in conformity and increase in the gradient index, violating major characteristics of SBRT. To minimize coverage loss due to small setup errors, a novel Restricted Single-Isocenter Stereotactic Body Radiotherapy (RESIST) treatment method was developed to provide efficient and effective treatments without substantially increasing treatment time. Lastly, RESIST was automated in the treatment planning system to allow for efficient and accurate treatment planning for two lung lesion SBRT. Automation includes beam geometry, algorithm selection, and an in-house trained dose volume histogram estimation model to improve plan quality. Automated planning significantly improves treatment planning time and decreases the chance of planning errors. This treatment delivery framework allows all patients who are to be treated with SBRT to multiple lung lesions to be treated efficiently and effectively. Further development of RESIST for \u3e 2 lesions and multi-site SBRT merits further investigation

Brachytherapy Seed and Applicator Localization via Iterative Forward Projection Matching Algorithm using Digital X-ray Projections

Interstitial and intracavitary brachytherapy plays an essential role in management of several malignancies. However, the achievable accuracy of brachytherapy treatment for prostate and cervical cancer is limited due to the lack of intraoperative planning and adaptive replanning. A major problem in implementing TRUS-based intraoperative planning is an inability of TRUS to accurately localize individual seed poses (positions and orientations) relative to the prostate volume during or after the implantation. For the locally advanced cervical cancer patient, manual drawing of the source positions on orthogonal films can not localize the full 3D intracavitary brachytherapy (ICB) applicator geometry. A new iterative forward projection matching (IFPM) algorithm can explicitly localize each individual seed/applicator by iteratively matching computed projections of the post-implant patient with the measured projections. This thesis describes adaptation and implementation of a novel IFPM algorithm that addresses hitherto unsolved problems in localization of brachytherapy seeds and applicators. The prototype implementation of 3-parameter point-seed IFPM algorithm was experimentally validated using a set of a few cone-beam CT (CBCT) projections of both the phantom and post-implant patient’s datasets. Geometric uncertainty due to gantry angle inaccuracy was incorporated. After this, IFPM algorithm was extended to 5-parameter elongated line-seed model which automatically reconstructs individual seed orientation as well as position. The accuracy of this algorithm was tested using both the synthetic-measured projections of clinically-realistic Model-6711 125I seed arrangements and measured projections of an in-house precision-machined prostate implant phantom that allows the orientations and locations of up to 100 seeds to be set to known values. The seed reconstruction error for simulation was less than 0.6 mm/3o. For the physical phantom experiments, IFPM absolute accuracy for position, polar angle, and azimuthal angel were (0.78 ± 0.57) mm, (5.8 ± 4.8)o, and (6.8 ± 4.0)o, respectively. It avoids the need to match corresponding seeds in each projection and accommodates incomplete data, overlapping seed clusters, and highly-migrated seeds. IFPM was further generalized from 5-parameter to 6-parameter model which was needed to reconstruct 3D pose of arbitrary-shape applicators. The voxelized 3D model of the applicator was obtained from external complex combinatorial geometric modeling. It is then integrated into the forward projection matching method for computing the 2D projections of the 3D ICB applicators, iteratively. The applicator reconstruction error for simulation was about 0.5 mm/2o. The residual 2D registration error (positional difference) between computed and actual measured applicator images was less than 1 mm for the intrauterine tandem and about 1.5 mm for the bilateral colpostats in each detector plane. By localizing the applicator’s internal structure and the sources, the effect of intra and inter-applicator attenuation can be included in the resultant dose distribution and CBCT metal streaking artifact mitigation. The localization accuracy of better than 1 mm and 6o has the potential to support more accurate Monte Carlo-based or 2D TG-43 dose calculations in clinical practice. It is hoped the clinical implementation of IFPM approach to localize elongated line-seed/applicator for intraoperative brachytherapy planning may have a positive impact on the treatment of prostate and cervical cancers

Real-time tumor localization with electromagnetic transponders for image-guided radiotherapy applications

The detection of intrafraction organ motion, necessary for the minimization of treatment errors, is a remaining challenge in radiotherapy. A novel technology for the dynamic monitoring of tumor motion uses tumor-implanted electromagnetic (EM) transponders. In the present thesis, concepts and strategies for the use of the EM technology in image-guided radiotherapy (IGRT) are developed. First, the compatibility of the EM technology with the radiotherapy environment is investigated experimentally. Subsequently, a technique is developed that combines EM tumor localization with the x-ray imaging options of IGRT. This technique exploits the unique advantages of EM tumor localization (non-ionizating radiation, three-dimensional target localization) and those of x-ray imaging (volumetric information about organ deformation and rotation, localization of organs at risk). The technique has been applied successfully to the elimination of motion artifacts in cone-beam computed tomography. In addition, the real-time control of a dynamic multileaf collimator based on the EM transponders could be demonstrated. Finally, the EM tumor tracking technology is introduced clinically with a study on prostate motion. The concepts developed in this thesis improve the detection of intrafraction organ motion in IGRT and thus enable the treatment of dynamic target volumes with increased accuracy

The Estimation and Correction of Rigid Motion in Helical Computed Tomography

X-ray CT is a tomographic imaging tool used in medicine and industry. Although technological developments have significantly improved the performance of CT systems, the accuracy of images produced by state-of-the-art scanners is still often limited by artefacts due to object motion. To tackle this problem, a number of motion estimation and compensation methods have been proposed. However, no methods with the demonstrated ability to correct for rigid motion in helical CT scans appear to exist. The primary aims of this thesis were to develop and evaluate effective methods for the estimation and correction of arbitrary six degree-of-freedom rigid motion in helical CT. As a first step, a method was developed to accurately estimate object motion during CT scanning with an optical tracking system, which provided sub-millimetre positional accuracy. Subsequently a motion correction method, which is analogous to a method previously developed for SPECT, was adapted to CT. The principle is to restore projection consistency by modifying the source-detector orbit in response to the measured object motion and reconstruct from the modified orbit with an iterative reconstruction algorithm. The feasibility of this method was demonstrated with a rapidly moving brain phantom, and the efficacy of correcting for a range of human head motions acquired from healthy volunteers was evaluated in simulations. The methods developed were found to provide accurate and artefact-free motion corrected images with most types of head motion likely to be encountered in clinical CT imaging, provided that the motion was accurately known. The method was also applied to CT data acquired on a hybrid PET/CT scanner demonstrating its versatility. Its clinical value may be significant by reducing the need for repeat scans (and repeat radiation doses), anesthesia and sedation in patient groups prone to motion, including young children

EPID-a useful interfraction QC tool

Biomedical accelerators used in radiotherapy are equipped with detector arrays which are commonly used to obtain the image of patient position during the treatment session. These devices use both kilovolt and megavolt x-ray beams. The advantage of EPID (Electronic Portal Imaging Device) megavolt panels is the correlation of the measured signal with the calibrated dose. The EPID gives a possibility to verify delivered dose. The aim of the study is to answer the question whether EPID can be useful as a tool for interfraction QC (quality control) of dose and geometry repeatability. The EPID system has been calibrated according to the manufacturer's recommendations to obtain a signal and dose values correlation. Initially, the uncertainty of the EPID matrix measurement was estimated. According to that, the detecting sensitivity of two parameters was checked: discrepancies between the planned and measured dose and field geometry variance. Moreover, the linearity of measured signal-dose function was evaluated. In the second part of the work, an analysis of several dose distributions was performed. In this study, the analysis of clinical cases was limited to stereotactic dynamic radiotherapy. Fluence maps were obtained as a result of the dose distribution measurements with the EPID during treatment sessions. The compatibility of fluence maps was analyzed using the gamma index. The fluence map acquired during the first fraction was the reference one. The obtained results show that EPID system can be used for interfraction control of dose and geometry repeatability

Real-time tumor localization with electromagnetic transponders for image-guided radiotherapy applications

The detection of intrafraction organ motion, necessary for the minimization of treatment errors, is a remaining challenge in radiotherapy. A novel technology for the dynamic monitoring of tumor motion uses tumor-implanted electromagnetic (EM) transponders. In the present thesis, concepts and strategies for the use of the EM technology in image-guided radiotherapy (IGRT) are developed. First, the compatibility of the EM technology with the radiotherapy environment is investigated experimentally. Subsequently, a technique is developed that combines EM tumor localization with the x-ray imaging options of IGRT. This technique exploits the unique advantages of EM tumor localization (non-ionizating radiation, three-dimensional target localization) and those of x-ray imaging (volumetric information about organ deformation and rotation, localization of organs at risk). The technique has been applied successfully to the elimination of motion artifacts in cone-beam computed tomography. In addition, the real-time control of a dynamic multileaf collimator based on the EM transponders could be demonstrated. Finally, the EM tumor tracking technology is introduced clinically with a study on prostate motion. The concepts developed in this thesis improve the detection of intrafraction organ motion in IGRT and thus enable the treatment of dynamic target volumes with increased accuracy

Development and Realization of the IGRT Inline Concept

A new concept for the integration of an imaging system into a medical linear accelerator for radiotherapy is presented, and its technical realization is described. An x-ray tube and a flat panel detector were installed along the treatment beam axis, such that the detector could not only be used for x-ray imaging of patients lying on the treatment couch, but also to measure the primary fluence of the therapy beam. The imaging system was synchronized with the linear accelerator by means of several hardware and software components that were developed as a part of this work in order to allow, for instance, the acquisition of fluoroscopic image sequences during beam delivery and the acquisition of volumetric cone beam CT information. Furthermore, external patient monitoring systems were integrated for respiration triggered imaging. Several applications and investigations about image quality, about the application of the images for the concepts of Adaptive Radiotherapy, and about the improvement of image quality were carried out using the new system. Furthermore, first feasibility studies with patients were performed, that combine imaging and therapy at the linac, in order to provide a higher precision for the beam delivery. Finally, the first commercial prototype, following the described concept, is presented

New Methods for Motion Management During Radiation Therapy

In this thesis, a number of new image-based techniques for the management of intrafractional motion during radiation therapy are presented. Intra-fractional motion describes all kinds of anatomy changes - most prominently respiration - that occur during a single treatment session. Spatially confining the radiation dose to the tumour tissue and thus sparing surrounding healthy tissue is assumed to be crucial for a successful treatment with limited side effects. Unfortunately, the delivery of dose distributions that are sharply confined to the tumour is greatly complicated by patient motion. If not accounted for, this motion will lead to a smearing out of the original dose distribution and will facilitate the redistribution of dose from tumour to healthy tissue. Possible technical solutions for this issue include the interruption of the radiation delivery if the tumour leaves a predefined spatial ‘window’, and the reshaping of the treatment field ‘on-the-fly’ to follow the tumour. Regardless of which delivery techniques is selected, the patient motion needs to be reliably detected in real-time to allow for an adaptation of the treatment delivery. First, we present experimental results for a novel x-ray imaging system that is attached to the treatment delivery device and enables us to continuously monitor the tumour motion during treatment delivery with sub-mm accuracy, a latency better than 90 ms, and a 7 Hz update rate. Second, we present a Monte Carlo simulation for an improved amorphous-silicon flat-panel detector that reduced treatment beam filtration by 60% and long-range MV-scatter by 80%. We conclude this thesis by presenting results of an experimental demonstration of a novel dose-saving actively-triggered 4d cone-beam computed tomography device

High-quality computed tomography using advanced model-based iterative reconstruction

Computed Tomography (CT) is an essential technology for the treatment, diagnosis, and study of disease, providing detailed three-dimensional images of patient anatomy. While CT image quality and resolution has improved in recent years, many clinical tasks require visualization and study of structures beyond current system capabilities. Model-Based Iterative Reconstruction (MBIR) techniques offer improved image quality over traditional methods by incorporating more accurate models of the imaging physics. In this work, we seek to improve image quality by including high-fidelity models of CT physics in a MBIR framework. Specifically, we measure and model spectral effects, scintillator blur, focal-spot blur, and gantry motion blur, paying particular attention to shift-variant blur properties and noise correlations. We derive a novel MBIR framework that is capable of modeling a wide range of physical effects, and use this framework with the physical models to reconstruct data from various systems. Physical models of varying degrees of accuracy are compared with each other and more traditional techniques. Image quality is assessed with a variety of metrics, including bias, noise, and edge-response, as well as task specific metrics such as segmentation quality and material density accuracy. These results show that improving the model accuracy generally improves image quality, as the measured data is used more efficiently. For example, modeling focal-spot blur, scintillator blur, and noise iicorrelations enables more accurate trabecular bone visualization and trabecular thickness calculation as compared to methods that ignore blur or model blur but ignore noise correlations. Additionally, MBIR with advanced modeling typically outperforms traditional methods, either with more accurate reconstructions or by including physical effects that cannot otherwise be modeled, such as shift-variant focal-spot blur. This work provides a means to produce high-quality and high-resolution CT reconstructions for a wide variety of systems with different hardware and geometries, providing new tradeoffs in system design, enabling new applications in CT, and ultimately improving patient care