Dosimetric Algorithm to Reproduce Isodose Curves Obtained from a LINAC

In this work isodose curves are obtained by the use of a new dosimetric algorithm using numerical data from percentage depth dose (PDD) and the maximum absorbed dose profile, calculated by Monte Carlo in a 18 MV LINAC. The software allows reproducing the absorbed dose percentage in the whole irradiated volume quickly and with a good approximation. To validate results an 18 MV LINAC with a whole geometry and a water phantom were constructed. On this construction, the distinct simulations were processed by the MCNPX code and then obtained the PDD and profiles for the whole depths of the radiation beam. The results data were used by the code to produce the dose percentages in any point of the irradiated volume. The absorbed dose for any voxel’s size was also reproduced at any point of the irradiated volume, even when the voxels are considered to be of a pixel’s size. The dosimetric algorithm is able to reproduce the absorbed dose induced by a radiation beam over a water phantom, considering PDD and profiles, whose maximum percent value is in the build-up region. Calculation time for the algorithm is only a few seconds, compared with the days taken when it is carried out by Monte Carlo

Clinical Implementation of Hypofractionated Radiation therapy for Lung Malignancies

For patients with oligometastases, metastases limited in number and site, the use of radiation therapy treatment with a hypofractionated dose scheme has been proposed as a potential ablative approach. There are a limited number of prospective studies looking at hypofractionated radiation therapy (HRT) for lung oligometastasis. Normal lung tissue complication and radiation planning technique are significant limiting factors for the implementation of hypofractionated lung metastasis. The problem statement of this study is how to improve the clinical implementation of HRT for lung metastasis exploring lung toxicity predictors, and developing an efficient radiation planning method. In the first study, we analyzed the dose distribution for 28 patients with lung oligometastasis and treated with HRT to multiple metastases in the lungs. We identified several significant predictors for lung radiation pneumonitis (RP) including the mean lung dose (MLD), V13 and V20. In addition a dose-effect relation between the lung normalized total dose (NTD) and RP may exist up to 48 Gy in three fractions. The dose-response parameters derived in our study appear to agree with other hypofractionated results published in the literature. In the second study, we used an inverse planning algorithm to develop a new radiation planning method by limiting the number of segments per beam angle down to 1 segment. Single segment plans were able to significantly improve tumor coverage and conformality, reduce the risk of lung RP, while simplifying the planning process and delivery. Target conformality and normal lung tissue sparing did not gain much improvement from an increase of plan complexity to five segments over the simplified one segment technique. The automation of our method is a good alternative to more traditional methods and offers significant dosimetric benefits. In the third study, we verified the single segment planning technique via patient specific quality assurance (QA) in a motion phantom. We found good agreement between calculated and measured doses via thermoluminescent detectors (TLD) inside the target. A dose to distance agreement of 3%/3 mm and 2%/2 mm between calculation and film measurements for representative plans in a motion phantom was verified at 98.99% and 97.15%, respectively

DEVELOPMENT AND CLINICAL VALIDATION OF KNOWLEDGE-BASED PLANNING MODELS FOR STEREOTACTIC BODY RADIOTHERAPY OF EARLY-STAGE NON-SMALL-CELL LUNG CANCER PATIENTS

Lung stereotactic body radiotherapy (SBRT) is a viable alternative to surgical intervention for the treatment of early-stage non-small-cell lung cancer (NSCLC) patients. This therapy achieves strong local control rates by delivering ultra-high, conformal radioablative doses in typically one to five fractions. Historically, lung SBRT plans are manually generated using 3D conformal radiation therapy, dynamic conformal arcs (DCA), intensity-modulated radiation therapy, and more recently via volumetric modulated arc therapy (VMAT) on a C-arm linear accelerator (linac). Manually planned VMAT is an advanced technique to deliver high-quality lung SBRT due to its dosimetric capabilities and utilization of flattening-filter free beams to improve patient compliance. However, there are limitations in manual treatment planning as the final plan quality heavily depends on a planner’s skill and available planning time. This could subject the plan quality to inter-planner variability from a single institution with multiple planners. Generally, the standard lung SBRT patient ‘simulation-to-treatment’ time is 7 working days. This delays clinic workflow and degrades the quality of treatment by eliminating adaptive re-planning capabilities. There is an ongoing effort to automate treatment planning by creating a model library of previously treated, high-quality plans and using it to prospectively generate new plans termed model-based knowledge-based planning (KBP). KBP aims to mitigate the previously mentioned limitations of manual planning and improve clinic workflow. As part of this dissertation, lung SBRT KBP models were created using a commercially available KBP engine that was trained using non-coplanar VMAT lung SBRT plans with the final dose reported from an advanced Acuros-based algorithm. The dissertation begins with the development of a robust and adaptable lung SBRT KBP model for early-stage, centrally-located NSCLC tumors that is fully compliant with Radiation Therapy Oncology Group (RTOG)-0813 protocol’s requirements. This new model provided similar or better plan quality to clinical plans, however it significantly increased total monitor units and plan complexity. This prompted the development and validation of an automated KBP routine for SBRT of peripheral lung tumors via DCA-based VMAT per RTOG-0618 criteria. This planning routine helped incorporate a historical DCA-based treatment planning approach with a VMAT optimization automated KBP engine that helps reduce plan complexity. For both central and peripheral lung lesions, the validated models are able to generate high-quality, standardized plans in under 30 min with minimal planner effort compared to an estimated 129 ± 34 min of a dedicated SBRT planner’s time. In practice, planners are expected to meticulously work on multiple plans at once, significantly increasing manual planning time. Thus, these KBP models will shorten the ‘simulation-to-treatment’ time down to as few as 3 working days, reduce inter-planer variability and improve patient safety. This will help standardize clinics and enable offline adaptive re-planning of lung SBRT treatment to account for physiological changes errors resulting from improper patient set-up. Lastly, this dissertation sought to further expand these KBP models to support delivering lung SBRT treatments on a new O-ring linac that was recently introduced to support underserved areas and fast patient throughput. Despite learning from a C-arm modality training dataset, these KBP models helped the O-ring linac to become a viable treatment modality for lung SBRT by providing an excellent plan quality similar to a C-arm linac in under 30 min. These KBP models will facilitate the easy transfer of patients across these diverse modalities and will provide a solution to unintended treatment course disruption due to lengthy machine downtime. Moreover, they will relieve the burden on a single machine in a high-volume lung SBRT clinic. Further adaptation and validation of these KBP models for large lung tumors (\u3e 5 cm) with multi-level dosing scheme and synchronous multi-lesion lung SBRT is ongoing

GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy

Online adaptive radiation therapy (ART) has great promise to significantly reduce normal tissue toxicity and/or improve tumor control through real-time treatment adaptations based on the current patient anatomy. However, the major technical obstacle for clinical realization of online ART, namely the inability to achieve real-time efficiency in treatment re-planning, has yet to be solved. To overcome this challenge, this paper presents our work on the implementation of an intensity modulated radiation therapy (IMRT) direct aperture optimization (DAO) algorithm on graphics processing unit (GPU) based on our previous work on CPU. We formulate the DAO problem as a large-scale convex programming problem, and use an exact method called column generation approach to deal with its extremely large dimensionality on GPU. Five 9-field prostate and five 5-field head-and-neck IMRT clinical cases with 5\times5 mm2 beamlet size and 2.5\times2.5\times2.5 mm3 voxel size were used to evaluate our algorithm on GPU. It takes only 0.7~2.5 seconds for our implementation to generate optimal treatment plans using 50 MLC apertures on an NVIDIA Tesla C1060 GPU card. Our work has therefore solved a major problem in developing ultra-fast (re-)planning technologies for online ART

Monte Carlo simulations for dosimetric verification in photon and electron beam radiotherapy

Dissertação para obtenção do Grau de Doutor em Engenharia BiomédicaOne of the primary requirements for successful radiotherapy treatments is the accurate calculation of dose distributions in the treatment planning process. Monte Carlo (MC) dose calculation algorithms are currently recognized as the most accurate method to meet this requirement and to increase even further dose accuracy. The improvements in computer processor technology and the development of variance reduction techniques for calculations have led to the recent implementation and use of MC algorithms for radiotherapy treatment planning at many clinical departments. The work conducting to the present thesis consists of several dosimetric studies which demonstrate the potential use of MC dose calculations as a robust tool of dose verification in two different fields of external radiotherapy: electron and photon beam radiotherapy. The first purpose of these studies is to evaluate dose distributions in challenging situations where conventional dose calculation algorithms have shown some limitations and it is very difficult to measure using typical clinical dosimetric procedures, namely in regions containing tissue inhomogeneities, such as air cavities and bones, and in superficial regions. A second goal of the present work is to use MC simulations to provide a detailed characterization of photon beams collimated by a multileaf collimator (MLC) in order to assess the dosimetric influences of these devices for the MC modeling of Intensity Modulated Radiotherapy (IMRT) plans. Detailed MC model of a Varian 2100 C/D linear accelerator and the Millenium MLC incorporated in the treatment head is accurately verified against measurements performed with ionization chambers and radiographic films. Finally, it is also an aim of this thesis to make a contribution for solving one of the current problems associated with the implementation and use of the MC method for radiotherapy treatment planning, namely the clinical impact of converting dose-to-medium to dose-to-water in treatment planning and dosimetric evaluation. For this purpose, prostate IMRT plans previously generated by a conventional dose algorithm are validated with the MC method using an alternative method, which involves the use of non-standard CT conversion ramps to create CT-based simulation phantoms.Fundação para a Ciência e Tecnologia; Centro de Física Nuclear da Universidade de Lisbo

Optimization of Treatment Geometry to Reduce Normal Brain Dose in Radiosurgery of Multiple Brain Metastases with Single-Isocenter Volumetric Modulated Arc Therapy

Treatment of patients with multiple brain metastases using a single-isocenter volumetric modulated arc therapy (VMAT) has been shown to decrease treatment time with the tradeoff of larger low dose to the normal brain tissue. We have developed an efficient Projection Summing Optimization Algorithm to optimize the treatment geometry in order to reduce dose to normal brain tissue for radiosurgery of multiple metastases with single-isocenter VMAT. The algorithm: (a) measures coordinates of outer boundary points of each lesion to be treated using the Eclipse Scripting Application Programming Interface, (b) determines the rotations of couch, collimator, and gantry using three matrices about the cardinal axes, (c) projects the outer boundary points of the lesion on to Beam Eye View projection plane, (d) optimizes couch and collimator angles by selecting the least total unblocked area for each specific treatment arc, and (e) generates a treatment plan with the optimized angles. The results showed significant reduction in the mean dose and low dose volume to normal brain, while maintaining the similar treatment plan qualities on the thirteen patients treated previously. The algorithm has the flexibility with regard to the beam arrangements and can be integrated in the treatment planning system for clinical application directly

Towards on-line plan adaptation of unified intensity-modulated arc therapy using a fast-direct aperture optimization algorithm

External beam radiotherapy (EBRT) plays a vital role in the treatment of cancer, with close to half of all cancer patients receiving EBRT at some point over their course of treatment. Although EBRT is a well-established form of treatment, there are a number of ways in which EBRT could still be improved in terms of quality and efficiency for treatment planning and radiation dose delivery. This thesis reports a series of improvements made to EBRT. First, we developed and evaluated a new treatment planning technique called unified intensity-modulated arc therapy (UIMAT) which combines the optimization and delivery of rotational volumetric modulated arc therapy (VMAT) and fixed-gantry intensity-modulated radiation therapy (IMRT). When retrospectively compared to clinical treatment plans using VMAT or IMRT alone, UIMAT plans reduced the dose to nearby critical structures by as much as 23% without compromising tumour volume coverage. The UIMAT plans were also more efficient to deliver. The reduction in normal tissue dose could help lower the probability of treatment-related toxicities, or alternatively could be used to improve tumour control probability, via dose escalation, while maintaining current dose limits for organs at risk. Second, we developed a new fast inverse direct aperture optimization (FIDAO) algorithm for IMRT, VMAT, and UIMAT treatment planning. FIDAO introduces modifications to the direct aperture optimization (DAO) process that help improve its computational efficiency. As demonstrated in several test cases, these modifications do not significantly impact the plan quality but reduced the DAO time by as much as 200-fold. If implemented with graphical processing units (GPUs), this project may allow for applications such as on-line treatment adaptation. Third, we investigated a method of acquiring tissue density information from cone-beam computed tomography (CBCT) datasets for on-line dose calculations, plan assessment, and potentially plan adaptation using FIDAO. This calibration technique accounts for patient-specific scattering conditions, demonstrated high dosimetric accuracy, and can be easily automated for on-line plan assessment. Collectively, these three projects will help reduce the normal tissue doses from EBRT, improve the planning and delivery efficiency, and pave the way for application like on-line plan assessment and adaptive radiotherapy in response to anatomical changes

Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation

What is an acceptably smoothed fluence? Dosimetric and delivery considerations for dynamic sliding window IMRT

<p>Abstract</p> <p>Background</p> <p>The study summarised in this report aimed to investigate the interplay between fluence complexity, dose calculation algorithms, dose calculation spatial resolution and delivery characteristics (monitor units, effective field width and dose delivery against dose prediction agreement) was investigated. A sample set of complex planning cases was selected and tested using a commercial treatment planning system capable of inverse optimisation and equipped with tools to tune fluence smoothness.</p> <p>Methods</p> <p>A set of increasingly smoothed fluence patterns was correlated to a generalised expression of the Modulation Index (MI) concept, in nature independent from the specific planning system used that could therefore be recommended as a predictor to score fluence "quality" at a very early stage of the IMRT QA process. Fluence complexity was also correlated to delivery accuracy and characteristics in terms of number of MU, dynamic window width and agreement between calculation and measurement (expressed as percentage of field area with a <it>γ </it>> 1 (%FA)) when comparing calculated vs. delivered modulated dose maps. Different resolutions of the calculation grid and different photon dose algorithms (pencil beam and anisotropic analytical algorithm) were used for the investigations.</p> <p>Results and Conclusion</p> <p>i) MI can be used as a reliable parameter to test different approaches/algorithms to smooth fluences implemented in a TPS, and to identify the preferable default values for the smoothing parameters if appropriate tools are implemented; ii) a MI threshold set at MI < 19 could ensure that the planned beams are safely and accurately delivered within stringent quality criteria; iii) a reduction in fluence complexity is strictly correlated to a corresponding reduction in MUs, as well as to a decrease of the average sliding window width (for dynamic IMRT delivery); iv) a smoother fluence results in a reduction of dose in the healthy tissue with a potentially relevant clinical benefit; v) increasing the smoothing parameter s, MI decreases with %FA: fluence complexity has a significant impact on the accuracy of delivery and the agreement between calculation and measurements improves with the advanced algorithms.</p

Depth Modulation in Radiotherapy

Intensity Modulated Radiotherapy (IMRT) has been a major field of research over the last thirty years and is today the standard in radiotherapy treatment of cancer. The introduction of IMRT into the clinical environment has greatly improved the ability of the treatment team to conform the radiation dose to the tumour volume. Alongside improvements in image guidance, IMRT has led to a reduction in side effects for patients and opened up the possibilities of dose escalation and hypofractionation. IMRT is however by no means perfect. IMRT and derivatives such as Volumated Arc Therapy (VMAT) are limited by the exit dose from the X-ray beams and deliver a significant amount of radiation dose to normal tissues. The much publicised alternative to IMRT is proton therapy. Proton therapy beams deposit dose over a narrow range resulting in minimal exit dose. The future of radiotherapy certainly involves a significant contribution from proton therapy but the availability to patients is likely to remain limited for a long time to come. The research in this thesis considers the possibility of further improving IMRT by modulating radiotherapy beams along their direction of travel as well as across their intensity, i.e. the so called ‘Depth Modulation’ of the thesis title. Although there are numerous possible ways to achieve depth modulation, this work proposes a combination of X-ray beams with electron beams of different energies with both modalities delivered with a conventional medical linear accelerator. The research in this thesis is concerned with developing a proof of principle for this method. It is to some extent a theoretical study, however at each step the possibility of practical implementation has been considered with the view that the method is only a viable proposition if it can be effectively implemented into clinical practice. The technique proposed in this work is to use electron beams delivered through X-ray MLC with a standard patient set up. To reduce scatter and photon contamination it is proposed to remove the scattering foils from the beamline and to employ optimisation of the electron and photon components to compensate for any remaining penumbra broadening. The research has shown that improvements to dosimetry through removal of the scattering foil would allow delivery without reducing the source to surface distance, making a single isocentre synergistic delivery for both the electron and photon components practical. Electron dose segments have been calculated using Monte Carlo radiation transport and a procedure to optimise dose for the combined photon and electron IMRT technique has been developed. Through development of the optimisation procedure the characteristics of the mixed modality technique have been examined. A number of findings are demonstrated such as the benefit of gaps between electron segments, the benefits of optimising for energy in three dimensions and the dependence of the cost function minimum on the electron to photon ratio. Through clinical examples it has been shown that for tumours close to the surface the mixed modality technique has the potential to reduce the dose to normal tissues, particular in the low dose wash. Calculations of relative malignant induction probability demonstrate that this reduction in dose has the potential to reduce the incidence of secondary cancer induction. Possible treatment sites for application of the technique include breast, head and neck, brain and sarcomas