Automatic Configuration of Fast Automated Multi‐Objective Treatment Planning in Radiotherapy

At Erasmus MC, automated plan generation is used to treat cancer patients. The system for automated planning is called Erasmus-iCycle which is used to consistently generate a high-quality and Pareto-optimal treatment plan with optimized beam directions for each patient. In this thesis, a new planning method, the lexicographic reference point method (LRPM), was developed and implemented in Erasmus-iCycle. The LRPM aims to improve the clinically used planning method in Erasmus-iCycle in two ways. Firstly, the LRPM should decrease the computation time of automatically generating a plan without compromising in

Automatic configuration of the reference point method for fully automated multi-objective treatment planning applied to oropharyngeal cancer

Purpose: In automated treatment planning, configuration of the underlying algorithm to generate high-quality plans for all patients of a particular tumor type can be a major challenge. Often, a time-consuming trial-and-error tuning procedure is required. The purpose of this paper is to automatically configure an automated treatment planning algorithm for oropharyngeal cancer patients. Methods: Recently, we proposed a new procedure to automatically configure the reference point method (RPM), a fast automatic multi-objective treatment planning algorithm. With a well-tuned configuration, the RPM generates a single Pareto optimal treatment plan with clinically favorable trade-offs for each patient. The automatic configuration of the RPM requires a set of computed tomography (CT) scans with corresponding dose distributions for training. Previously, we demonstrated for prostate cancer planning with 12 objectives th

Online-adaptive versus robust IMPT for prostate cancer: How much can we gain?

Background/purpose: Intensity-modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. Available mitigation techniques include robust treatment planning and online-adaptive IMPT. This study compares a robust planning strategy to two online-adaptive IMPT strategies to determine the benefit of online adaptation. Materials/methods: We derived the robustness settings and safety margins needed to yield adequate target coverage (V95% 98%) for >90% of 11 patients in a prostate cancer cohort (88 repeat CTs). For each patient, we also adapted a non-robust prior plan using a simple restoration and a full adaptation method. The restoration uses energy-adaptation followed by a fast spot-intensity re-optimization. The full adaptation uses energy-adaptation followed by the addition of new spots and a range-robust spot-intensity optimization. Dose was prescribed as 55 Gy(RBE) to the low-dose target (lymph nodes and seminal vesicles) with a boost to 74 Gy(RBE) to the high-dose target (prostate). Daily patient set-up was simulated using implanted intra-prostatic markers.

Plan-library supported automated replanning for online-adaptive intensity-modulated proton therapy of cervical cancer

Background: Intensity-modulated proton therapy is sensitive to inter-fraction variations, including density changes along the pencil-beam paths and variations in organ-shape and location. Large dayto-day variations are seen for cervical cancer patients. The purpose of this study was to develop and evaluate a novel method for online selection of a plan from a patient-specific library of prior plans for different anatomies, and adapt it for the daily anatomy. Material and methods: The patient-specific library of prior plans accounting for altered target geometries was generated using a pretreatment established target motion model. Each fraction, the best fitting prior plan was selected. This prior plan was adapted using (1) a restoration of spot-positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast optimization of the spot-weights with the reference point method (RPM) to obtain a Pareto-optimal plan for the daily anatomy. Spot addition and spot-weight optimization could be repeated iteratively. The patient cohort consisted of six patients with in total 23 repeat-CT scans, with a prescribed dose of 45 Gy(RBE) to the primary tumor and the nodal CTV. Using a 1-plan-library (one prior plan based on all motion in the motion model) was compared to choosing from a 2-plan-library (two prior plans based on part of the motion). Results: Applying the prior-plan adaptation method with one iteration of adding spots resulted in clinically acceptable target coverage (V95% 95% and V107% 2%) for 37/46 plans using the 1-planlibrary and 41/46 plans for the 2-plan-library. When adding spots twice, the 2-plan-library approach could obtain acceptable coverage for all scans, while the 1-plan-library approach showed V107% > 2% for 3/46 plans. Similar OAR results were obtained. Conclusion: The automated prior-plan adaptation method can successfully adapt for the large day-today variations observed in cervical cancer patients

Identification and thermochemical analysis of high-lignin feedstocks for biofuel and biochemical production

Background - Lignin is a highly abundant biopolymer synthesized by plants as a complex component of plant secondary cell walls. Efforts to utilize lignin-based bioproducts are needed. Results - Herein we identify and characterize the composition and pyrolytic deconstruction characteristics of high-lignin feedstocks. Feedstocks displaying the highest levels of lignin were identified as drupe endocarp biomass arising as agricultural waste from horticultural crops. By performing pyrolysis coupled to gas chromatography-mass spectrometry, we characterized lignin-derived deconstruction products from endocarp biomass and compared these with switchgrass. By comparing individual pyrolytic products, we document higher amounts of acetic acid, 1-hydroxy-2-propanone, acetone and furfural in switchgrass compared to endocarp tissue, which is consistent with high holocellulose relative to lignin. By contrast, greater yields of lignin-based pyrolytic products such as phenol, 2-methoxyphenol, 2-methylphenol, 2-methoxy-4-methylphenol and 4-ethyl-2-methoxyphenol arising from drupe endocarp tissue are documented. Conclusions - Differences in product yield, thermal decomposition rates and molecular species distribution among the feedstocks illustrate the potential of high-lignin endocarp feedstocks to generate valuable chemicals by thermochemical deconstruction

Metabolic engineering of Rhizopus oryzae for the production of platform chemicals

Rhizopus oryzae is a filamentous fungus belonging to the Zygomycetes. It is among others known for its ability to produce the sustainable platform chemicals l-(+)-lactic acid, fumaric acid, and ethanol. During glycolysis, all fermentable carbon sources are metabolized to pyruvate and subsequently distributed over the pathways leading to the formation of these products. These platform chemicals are produced in high yields on a wide range of carbon sources. The yields are in excess of 85 % of the theoretical yield for l-(+)-lactic acid and ethanol and over 65 % for fumaric acid. The study and optimization of the metabolic pathways involved in the production of these compounds requires well-developed metabolic engineering tools and knowledge of the genetic makeup of this organism. This review focuses on the current metabolic engineering techniques available for R. oryzae and their application on the metabolic pathways of the main fermentation products

Routh's stabiliteitscriterium voor convexe stabiliteitsgebieden

In dit project is onderzocht hoe stabiliteitscriteria afgeleid kunnen worden voor convexe gebieden in het complexe vlak.MathematicsElectrical Engineering, Mathematics and Computer Scienc

Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy

Treatment plan generation in radiation therapy is a multicriteria optimization problem, in which multiple, often conflicting, criteria need to be optimized simultaneously. Several methods can be used to obtain Pareto optimal treatment plans, meaning that no criterion can be improved without deteriorating another criterion. The focus is on the 2-phase ?-constraint (2p?c) method and the reference point method (RPM), which both automatically generate Pareto optimal intensity modulated radiation therapy (IMRT) plans. Although the plans of the 2p?c method are of high quality, several optimizations need to be performed. For the RPM, only a single optimization is needed per plan. The aim of this thesis is configure the RPM so that the resulting treatment plans are of the same quality as the treatment plans generated by the 2p?c method, and thereby reducing the computation time. The 2p?c method prioritizes the criteria and assigns goal values to them. Then, each criterion is iteratively optimized and constrained according to a rule (depending on whether the goal value was met or not). The number of optimizations needed scales linearly with the number of criteria. A specific configuration of the RPM, namely the lexicographic reference point method (LRPM), maintains the lexicographic ordering of the criteria. Both the 2p?c method and the LRPM have been tested on 30 prostate cancer patients and 2 head-and-neck cancer patients. For the 30 prostate cancer patients, all treatment plans generated by the LRPM were found of similar quality when compared to the plans generated by the 2p?c method. On average, the computation time of the LRPM was 3 minutes, which is a speed-up factor of nearly 12. For the 2 head-and-neck cancer patients, the plans of the LRPM were considered as good as or better than the plans of the 2p?c method with a speed-up factor for the computation time of 3-4.Applied mathematicsElectrical Engineering, Mathematics and Computer Scienc