Modelling the impact of treatment uncertainties in radiotherapy

Uncertainties are inevitably part of the radiotherapy process. Uncertainty in the dose deposited in the tumour exists due to organ motion, patient positioning errors, fluctuations in machine output, delineation of regions of interest, the modality of imaging used, and treatment planning algorithm assumptions among others; there is uncertainty in the dose required to eradicate a tumour due to interpatient variations in patient-specific variables such as their sensitivity to radiation; and there is uncertainty in the dose-volume restraints that limit dose to normal tissue. This thesis involves three major streams of research including investigation of the actual dose delivered to target and normal tissue, the effect of dose uncertainty on radiobiological indices, and techniques to display the dose uncertainty in a treatment planning system. All of the analyses are performed with the dose distribution from a four-field box treatment using 6 MV photons. The treatment fields include uniform margins between the clinical target volume and planning target volume of 0.5 cm, 1.0 cm, and 1.5 cm. The major work is preceded by a thorough literature review on the size of setup and organ motion errors for various organs and setup techniques used in radiotherapy. A Monte Carlo (MC) code was written to simulate both the treatment planning and delivery phases of the radiotherapy treatment. Using MC, the mean and the variation in treatment dose are calculated for both an individual patient and across a population of patients. In particular, the possible discrepancy in tumour position located from a single CT scan and the magnitude of reduction in dose variation following multiple CT scans is investigated. A novel convolution kernel to include multiple pretreatment CT scans in the calculation of mean treatment dose is derived. Variations in dose deposited to prostate and rectal wall are assessed for each of the margins and for various magnitudes of systematic and random error, and penumbra gradients. The linear quadratic model is used to calculate prostate Tumour Control Probability (TCP) incorporating an actual (modelled) delivered prostate dose. The Kallman s-model is used to calculate the normal tissue complication probability (NTCP), incorporating actual (modelled) fraction dose in the deforming rectal wall. The impact of each treatment uncertainty on the variation in the radiobiological index is calculated for the margin sizes.Thesis (Ph.D.)--Department of Physics and Mathematical Physics, 2002

The optimization of image guided radiotherapy in lung cancer

The hypothesis of this work was whether IGRT could be safely implemented for clinical use in a busy oncology centre. I aimed to study a number of questions that remain unresolved in the current literature regarding safe and optimised implementation of IGRT techniques. The first study undertaken was the calculation of a local set up margin using two widely recognised margin recipes. This involved the assessment and analysis of multiple images belonging to 100 patients. This allowed progression onto the next project which was assessment of the optimal safe method of delineation of 4DCT. The most efficient method was compared to gold standard. At this point a different aspect of the radiation process was assessed, namely verification. A feasibility study of a simple, efficient form of imaging for use in review of a particular error was performed. This also involved the use of a novel tool which required independent assessment. This progressed into a further study of a larger number of patients using this tool and the images assessed previously to verify a novel form of radiation delivery. Lastly a planning study was performed to quantify the clinical benefit of another delivery system. This involved the delineation and planning of a large number of radical lung patients with standard radiation treatment and the novel radiation treatment and an assessment of the potential clinical benefits. The work presented in this thesis has answered some specific questions in IGRT in lung cancer, and contributed both locally and in the wider lung cancer community to increasing the use of IGRT in lung cancer

A study of coverage optimized planning incorporating models of geometric uncertainties for prostate cancer

A fundamental challenge in the treatment planning process of multi-fractional external-beam radiation therapy (EBRT) is the tradeoff between tumor control and normal tissue sparing in the presence of geometric uncertainties (GUs). To accommodate GUs, the conventional way is to use an empirical planning treatment volume (PTV) margin on the treatment target. However, it is difficult to determine a near-optimal PTV margin to ensure specified target coverage with as much normal tissue protection as achievable. Coverage optimized planning (COP) avoids this problem by optimizing dose in possible virtual treatment courses with GU models directly incorporated. A near-optimal dosimetric margin generated by COP was reported to savvily accommodate setup errors of target and normal tissues for prostate cancer treatment. This work further develops COP to account for (1) deformable organ motion and (2) delineation uncertainties for high-risk prostate cancer patients. The clinical value of COP is investigated by comparing with two margin-based planning techniques: (i) optimized margin (OM) technique that iteratively modifies PTV margins according to the evaluated target coverage probability and (ii) fixed margin (FM) technique that uses empirically selected constant PTV margins. Without patient-specific coverage probability estimation, FM plans are always less immune to the degraded effect of the modeled GUs than the COP plans or the OM plans. Empirical PTV margins face more risks of undesirable target coverage probability and/or excessive dose to surrounding OAR. The value of COP relative to OM varies with different GUs. As implemented for deformable organ motions, COP has limited clinical benefit. Due to optimization tradeoffs, COP often results in target coverage probability below the prescribed value while OM achieves better target coverage with comparable normal tissue dose. For delineation uncertainties, the clinical value of COP is potentially significant. Compared to OM, COP successfully maintains acceptable target coverage probability by exploiting the slack of normal tissue dose in low dose regions and maximally limiting high dose to normal tissue within tolerance

Treatment planning optimisation in proton therapy

The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions

Optimizing Respiratory Gated Intensity Modulated Radiation Therapy Planning and Delivery of Early-Stage Non-Small Cell Lung Cancer

Stereotactic ablative body radiotherapy (SABR) is the standard of care for inoperable early-stage non-small cell lung cancer (NSCLC) patients. However, thoracic tumours are susceptible to respiratory motion and, if unaccounted for, can potentially lead to dosimetric uncertainties. Respiratory gating is one method that limits treatment delivery to portions of the respiratory cycle, but when combined with intensity-modulated radiotherapy (IMRT), requires rigorous verification. The goal of this thesis is to optimize respiratory gated IMRT treatment planning and develop image-guided strategies to verify the dose delivery for future early-stage NSCLC patients. Retrospective treatment plans were generated for various IMRT delivery techniques, including fixed-beam, volumetric modulated arc therapy (VMAT), and helical tomotherapy. VMAT was determined the best technique for optimizing dose conformity and efficiency. A second treatment planning study that considered patients exhibiting significant tumour motion was conducted. Respiratory ungated and gated VMAT plans were compared. Significant decreases in V20Gy and V50%, predictors for radiation pneumonitis and irreversible fibrosis, respectively, were observed. The predominant uncertainty of respiratory gating lies in the ability of an external surrogate marker to accurately predict internal target motion. Intrafraction triggered kV imaging was validated in a programmable motion phantom study as a method to determine how correlated the internal and external motion are during ungated and gated VMAT deliveries and to identify potential phase shifts between the motions. KV projections acquired during gated VMAT delivery were used to reconstruct gated cone-beam CT (CBCT), providing 3D tumour position verification. Image quality and target detectability, in the presence of MV scatter from the treatment beam to the kV detector, was evaluated with various imaging parameters and under real-patient breathing motion conditions. No significant difference in image quality was observed for the CBCT acquisitions with or without the presence of MV scatter. This thesis explores the benefits of combining respiratory gating with IMRT/VMAT for the treatment of early stage NSCLC with SABR, and evaluates advanced on-board imaging capabilities to develop dose delivery verification protocols. The results of this thesis will provide the tools necessary to confidently implement a respiratory gated radiotherapy program aimed at improving the therapeutic ratio for early-stage NSCLC

Statistical modeling of interfractional tissue deformation and its application in radiation therapy planning

In radiation therapy, interfraction organ motion introduces a level of geometric uncertainty into the planning process. Plans, which are typically based upon a single instance of anatomy, must be robust against daily anatomical variations. For this problem, a model of the magnitude, direction, and likelihood of deformation is useful. In this thesis, principal component analysis (PCA) is used to statistically model the 3D organ motion for 19 prostate cancer patients, each with 8-13 fractional computed tomography (CT) images. Deformable image registration and the resultant displacement vector fields (DVFs) are used to quantify the interfraction systematic and random motion. By applying the PCA technique to the random DVFs, principal modes of random tissue deformation were determined for each patient, and a method for sampling synthetic random DVFs was developed. The PCA model was then extended to describe the principal modes of systematic and random organ motion for the population of patients. A leave-one-out study tested both the systematic and random motion model’s ability to represent PCA training set DVFs. The random and systematic DVF PCA models allowed the reconstruction of these data with absolute mean errors between 0.5-0.9 mm and 1-2 mm, respectively. To the best of the author’s knowledge, this study is the first successful effort to build a fully 3D statistical PCA model of systematic tissue deformation in a population of patients. By sampling synthetic systematic and random errors, organ occupancy maps were created for bony and prostate-centroid patient setup processes. By thresholding these maps, PCA-based planning target volume (PTV) was created and tested against conventional margin recipes (van Herk for bony alignment and 5 mm fixed [3 mm posterior] margin for centroid alignment) in a virtual clinical trial for low-risk prostate cancer. Deformably accumulated delivered dose served as a surrogate for clinical outcome. For the bony landmark setup subtrial, the PCA PTV significantly (p30, D20, and D5 to bladder and D50 to rectum, while increasing rectal D20 and D5. For the centroid-aligned setup, the PCA PTV significantly reduced all bladder DVH metrics and trended to lower rectal toxicity metrics. All PTVs covered the prostate with the prescription dose

Accumulating delivered dose to the rectum to improve toxicity prediction in prostate radiotherapy

Accumulating delivered dose to the rectum to improve toxicity prediction in prostate radiotherapy Leila E. A. Shelley Gastrointestinal (GI) toxicity is a clinical issue suffered by up to 22% of prostate cancer radiotherapy patients. However, the relationship between radiation dose and toxicity is generally poorly understood. In prostate radiotherapy, the rectum is a dose-limiting structure to which treatment planning dose constraints are applied to minimise the risk of toxicity. Current normal tissue complication probability (NTCP) models are based on planned dose data and do not consider the effects of organ motion on true delivered dose. The VoxTox research programme has developed automated solutions for segmentation and dose calculation of the rectum for prostate cancer patients being treated with helical TomoTherapy. Daily image guidance scans, acquired primarily for the purposes of positional verification, are exploited by extracting quantitative information to facilitate the calculation of daily delivered and total accumulated dose to the rectum. Prospectively collected toxicity data at 2 years post-treatment were available for 295 patients across two separate cohorts. In this thesis, the hypothesis being tested is that delivered dose is a better predictor of rectal toxicity than planned dose in prostate radiotherapy. The research has successfully demonstrated, for the first time, that delivered dose produces stronger associations with rectal bleeding and proctitis than planned dose. Analysis was performed using dose surface maps (DSMs) of the rectal wall, allowing spatial aspects of dose to be retained during accumulation. A subsequent analysis on a separate cohort also found stronger links between delivered dose and GI toxicity, stool frequency, and bowel bother, in addition to rectal bleeding and proctitis. Biomechanical finite element (FE) modelling was introduced to provide a more anatomically plausible tool for dose accumulation and allowed more accurate tracking of dose at the voxel level. A sensitivity analysis was conducted which explored the effect of simulated rectal motion on dose, and corresponding change in NTCP. For VoxTox patient dose-toxicity analysis, further dose parameterisation approaches were explored in order to consider the increased resolution of information available. Voxel-based rectal subregions at risk (SRRs) were identified using geometric and statistical approaches. In general, discriminative power improved with FE modelling for both planned and accumulated delivered dose, and associations between accumulated dose and toxicity were strengthened by voxel-based subregion analysis. Multivariate NTCP models were constructed for 12 different toxicity endpoints based on planned and accumulated dose parameters. Model performance was compared between analysis approaches, and models were tested on a validation dataset. In general, FE-based dose models performed best, although the optimal dose parameter selected within the model varied with toxicity endpoint. Overall, results suggest that there is an advantage to incorporating delivered dose into NTCP modelling. However, the differences between planned and accumulated dose can be subtle. Meaningful parameterisation of accumulated dose needs careful consideration, as traditional methods for quantifying planned dose may not be directly transferable. Voxel-based analysis techniques are recommended in order to accurately preserve and register spatial dose information, and have been shown to improve the strength of dose-toxicity associations. Further research into quantifying voxel level dose distributions is encouraged. It is anticipated that the novel scientific contributions presented within this thesis will prove valuable for future development of clinical decision-making tools for adaptive radiotherapy, with the ultimate aim of reducing the incidence of radiation-induced toxicity for prostate cancer radiotherapy patients.Personal funding was provided by the WD Armstrong Trust. The VoxTox Research Programme was funded by Cancer Research UK

Three Essays on Radiotherapy Treatment Planning Optimization

Radiation therapy is one of the most common and effective methods of treating cancer. There are two main types: external and internal. External to the patient, a linear accelerator aims beams of radiation toward the patient; internal to the patient, radioactive sources are placed temporarily or permanently at the treatment site to deposit dose locally. Both methods of treatment can deliver complex dose distributions to a patient. The radiation damages both tumorous tissue and nearby healthy organs; treatment planning optimization determines how to deliver a dose distribution that maximizes tumor kill while sparing nearby healthy organs as much as possible. This thesis studies three treatment planning problems: the first two are in the context of external radiation therapy and the third is in the context of internal radiation therapy. Conventional planning is based on only the physical geometry of the patient anatomy. In chapter II, we propose two models that incorporate (additional) liver function information for planning liver cancer treatment to preserve as much post-treatment liver function as possible and compare this to a conventional approach that ignores liver function information. Conventional plans assume the patient geometry does not change between the time of patient imaging and later treatments. Although the patient geometry can be updated at treatment for plan adaptation, current practice may lead to plans that result in significantly worse quality than originally intended due to its myopic nature. In chapter III, we propose a model that produces a plan that caters to each potential patient geometry while considering both day-of and cumulative impact. In high-dose rate brachytherapy, the patient undergoes anesthesia due to the need to implant catheters for radiation source placement before planning. Consideration of multiple conflicting criteria in treatment planning results in challenging optimization problems. Current commercial systems require iterative guess-and-checking of optimization input parameters to make trade-offs among criteria, but a plan must be finalized quickly to minimize anesthesia administration. In chapter IV, we develop a practical optimization engine that generates a trade-off surface and feeds into a graphical user interface that provides the clinician more control to make trade-offs without trial-and-error optimizations.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/140827/1/vwwu_1.pd

The Nano-X Linear Accelerator: A Compact and Economical Cancer Radiotherapy System Incorporating Patient Rotation.

Rapid technological improvements in radiotherapy delivery results in improved outcomes to patients, yet current commercial systems with these technologies on board are costly. The aim of this study was to develop a state-of-the-art cancer radiotherapy system that is economical and space efficient fitting with current world demands. The Nano-X system is a compact design that is light weight combining a patient rotation system with a vertical 6 MV fixed beam. In this paper, we present the Nano-X system design configuration, an estimate of the system dimensions and its potential impact on shielding cost reductions. We provide an assessment of implementing such a radiotherapy system clinically, its advantages and disadvantages compared to a compact conventional gantry rotating linac. The Nano-X system has several differentiating features from current radiotherapy systems, it is [1] compact and therefore can fit into small vaults, [2] light weight, and [3] engineering efficient, i.e., it rotates a relatively light component and the main treatment delivery components are not under rotation (e.g., DMLCs). All these features can have an impact on reducing the costs of the system. In terms of shielding requirements, leakage radiation was found to be the dominant contributor to the Nano-X vault and as such no primary shielding was necessary. For a low leakage design, the Nano-X vault footprint and concrete volume required is 17 m2 and 35 m3 respectively, compared to 54 m2 and 102 m3 for a conventional compact linac vault, resulting in decreased costs in shielding. Key issues to be investigated in future work are the possible patient comfort concerns associated with the patient rotation system, as well as the magnitude of deformation and subsequent adaptation requirements

Strategies for Reducing the Impact of Tumour Motion During Helical Tomotherapy

Tumour motion presents a significant limitation for effective radiotherapy of lung cancer, and more specifically for helical tomotherapy. The simultaneous and continuous movements of tomotherapy subsystems (gantry, couch, and binary multi-leaf collimator) can lead to inaccurate dose delivery, when combined with tumour motion. In this thesis, we have investigated the impact of tumour motion and strategies to reduce the resulting dose discrepancies for helical tomotherapy, through computer simulations and film measurements performed in a dynamic body phantom. Three distinctively different types of dose discrepancies have been isolated: dose rounding, dose rippling, and the intensity-modulated radiation therapy (IMRT) asynchronization effect. Each effect was shown to be affected by different combinations of tumour motion and treatment parameters. In clinical practice using a conventional fractionation scheme, the dose rounding effect remains the major concern, which can be compensated by assigning a larger treatment margin around the tumour volume. For hypofractionation schemes, the IMRT asynchronization effect can become an additional concern by introducing dose discrepancies inside the target volume, necessitating the use of a motion management technique. Two new motion management techniques have thus been developed for helical tomotherapy: loose helical tomotherapy with breath-holding and multi-pass respiratory gating. Both methods require the treatment couch to be reset to its starting position to repeat the entire helical treatment, until nearly all planned dose is delivered. For sinusoidal target motion, employing multi-pass respiratory gating was shown to reduce the dose deviation inside the target volume from 14% to 2% for a single fraction, using 4 gated passes. For non-sinusoidal tumour motion causing a dose deviation of 6% within the tumour volume, the required number of passes to keep the dose deviation below 1% was approximately 4 passes for 30 fractions and 5 passes for 3 fractions, demonstrating the feasibility of the multi-pass respiratory gating approach. Clinical implementation of the multi-pass respiratory gating technique would require a number of electronic control and communication modifications to the existing tomotherapy machine, which would lead to significant improvements in the dose distributions delivered for lung tomotherapy treatments – especially for patients exhibiting large tumour motion who are treated with hypofractionation schemes