Data for TROTS – The Radiotherapy Optimisation Test Set

The Radiotherapy Optimisation Test Set (TROTS) is an extensive set of problems originating from radiotherapy (radiation therapy) treatment planning. This dataset is created for 2 purposes: (1) to supply a large-scale dense dataset to measure performance and quality of mathematical solvers, and (2) to supply a dataset to investigate the multi-criteria optimisation and decision-making nature of the radiotherapy problem. The dataset contains 120 problems (patients), divided over 6 different treatment protocols/tumour types. Each problem contains numerical data, a configuration for the optimisation problem, and data required to visualise and interpret the results. The data is stored as HDF5 compatible Matlab files, and includes scripts to work with the dataset

Evaluation of alternative parameter settings for dose restoration and full plan adaptation in IMPT for prostate cancer

Background/purpose: Intensity-modulated proton therapy is highly sensitive to anatomical variations. A dose restoration method and a full plan adaptation method have been developed earlier, both requiring several parameter settings. This study evaluates the validity of the previously selected settings by systematically comparing them to alternatives. Materials/methods: The dose restoration method takes a prior plan and uses an energy-adaptation followed by a spot-intensity re-optimization to restore the plan to its initial state. The full adaptation method uses an energy-adaptation followed by the addition of new spots and a spot-intensity optimization to fit the new anatomy. We varied: 1) The margins and robustness settings of the prior plan, 2) the spot-addition sample size, i.e. the number of added spots, 3) the spot-addition stopping criterion, and 4) the spot-intensity optimization approach. The last three were evaluated only for the full plan adaptation. Evaluations were done on 88 CT scans of 11 prostate cancer patients. Dose was prescribed as 55 Gy(RBE) to the lymph nodes and seminal vesicles with a boost to 74 Gy(RBE) to the prostate. Results: For the dose restoration method, changing the applied CTV-to-PTV margins and plan robustness in the prior plans yielded insufficient target coverage or increased OAR doses. For the full plan adaptation, more spot-addition iterations and using a different optimization approach resulted in lower OAR doses compared to the default settings while maintaining target coverage. However, the calculation times increased by up to 20 times, making these variations infeasible for online-adaptation. Conclusion: We recommend maintaining the default setting for the dose restoration approach. For the full plan adaptation we recommend to focus on fine-tuning the optimization-parameters, and apart from this using the default settings.</p

Nearshore marine ecology at Hutchinson Island, Florida: 1971-1974. VI. plankton dynamics, 1971-1973, VII. phytoplankton 1971-1973, VIII. zooplankton, 1971-1973, IX. diel plankton, 1973-1974, X. benthic algae species list

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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

Reducing the Risk of Secondary Lung Cancer in Treatment Planning of Accelerated Partial Breast Irradiation

Purpose: Adjuvant accelerated partial breast irradiation (APBI) results in low local recurrence risks. However, the survival benefit of adjuvant radiotherapy APBI for low-risk breast cancer might partially be offset by the risk of radiation-induced lung cancer. Reducing the lung dose mitigates this risk, but this could result in higher doses to the ipsilateral breast. Different external beam APBI techniques are equally conformal and homogenous, but the intermediate to low dose distribution differs. Thus, the risk of toxicity is different. The purpose of this study is to quantify the trade-off between secondary lung cancer risk and breast dose in treatment planning and to compare an optimal coplanar and non-coplanar technique. Methods: A total of 440 APBI treatment plans were generated using automated treatment planning for a coplanar VMAT beam-setup and a non-coplanar robotic stereotactic radiotherapy beam-setup. This enabled an unbiased comparison of two times 11 Pareto-optimal plans for 20 patie

Self-diffusion in dense granular shear flows

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We present experimental results on diffusivity in dense, granular shear in a 2D Couette geometry. We find that self-diffusivities are proportional to the local shear rate with diffusivities along the mean flow approximately twice as large as those in the perpendicular direction. The magnitude of the diffusivity is D \approx \dot\gamma a^2 where a is the particle radius. However, the gradient in shear rate, coupling to the mean flow, and drag at the moving boundary lead to particle displacements that can appear sub- or super-diffusive. In particular, diffusion appears superdiffusive along the mean flow direction due to Taylor dispersion effects and subdiffusive along the perpendicular direction due to the gradient in shear rate. The anisotropic force network leads to an additional anisotropy in the diffusivity that is a property of dense systems with no obvious analog in rapid flows. Specifically, the diffusivity is supressed along the direction of the strong force network. A simple random walk simulation reproduces the key features of the data, such as the apparent superdiffusive and subdiffusive behavior arising from the mean flow, confirming the underlying diffusive motion. The additional anisotropy is not observed in the simulation since the strong force network is not included. Examples of correlated motion, such as transient vortices, and Levy flights are also observed. Although correlated motion creates velocity fields qualitatively different from Brownian motion and can introduce non-diffusive effects, on average the system appears simply diffusive.Comment: 13 pages, 20 figures (accepted to Phys. Rev. E

Automated Radiotherapy Planning for Patient-Specific Exploration of the Trade-Off Between Tumor Dose Coverage and Predicted Radiation-Induced Toxicity-A Proof of Principle Study for Prostate Cancer

Background: Currently, radiation-oncologists generally evaluate a single treatment plan for each patient that is possibly adapted by the planner prior to final app