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

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

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

Validation of fully automated VMAT plan generation for library-based plan-of-the-day cervical cancer radiotherapy

Purpose: To develop and validate fully automated generation of VMAT plan-libraries for plan-of-the-day adaptive radiotherapy in locally-advanced cervical cancer. Material and Methods: Our framework for fully automated treatment plan generation (Erasmus-iCycle) was adapted to create dual-arc VMAT treatment plan libraries for cervical cancer patients. For each of 34 patients, automatically generated VMAT plans (autoVMAT) were compared to manually generated, clinically delivered 9-beam IMRT plans (CLINICAL), and to dual-arc VMAT plans generated manually by an expert planner (manVMAT). Furthermore, all plans were benchmarked against 20-beam equi-angular IMRT plans (autoIMRT). For all plans, a PTV coverage of 99.5% by at least 95% of the prescribed dose (46 Gy) had the highest planning priority, followed by minimization of V45Gy for small bowel (SB). Other OARs considered were bladder, rectum, and sigmoid. Results: All plans had a highly similar PTV coverage, within the clinical constraints (above). After plan normalizations for exactly equal median PTV doses in corresponding plans, all evaluated OAR parameters in autoVMAT plans were on average lower than in the CLINICAL plans with an average reduction in SB V45Gy of 34.6% (p<0.001). For 41/44 autoVMAT plans, SB V45Gy was lower than for manVMAT (p<0.001, average reduction 30.3%), while SB V15Gy increased by 2.3% (p = 0.011). AutoIMRT reduced SB V45Gy by another 2.7% compared to autoVMAT, while also resulting in a 9.0% reduction in SB V15Gy (p<0.001), but with a prolonged delivery time. Differences between manVMAT and autoVMAT in bladder, rectal and sigmoid doses were ≤ 1%. Improvements in SB dose delivery with autoVMAT instead of manVMAT were higher for empty bladder PTVs compared to full bladder PTVs, due to differences in concavity of the PTVs. sponsored the appointment of STH for this project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conclusions: Quality of automatically generated VMAT plans was superior to manually generated plans. Automatic VMAT plan generation for cervical cancer has been implemented in our clinical routine. Due to the achieved workload reduction, extension of plan libraries has become feasible

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.

Fully automated treatment planning of spinal metastases - A comparison to manual planning of Volumetric Modulated Arc Therapy for conventionally fractionated irradiation

_Background:_ Planning for Volumetric Modulated Arc Therapy (VMAT) may be time consuming and its use is limited by available staff resources. Automated multicriterial treatment planning can eliminate this bottleneck. We compared automatically created (auto) VMAT plans generated by Erasmus-iCycle to manually created VMAT plans for treatment of spinal metastases. _Methods:_ Forty-two targets in 32 patients were analyzed. Lungs and kidneys were defined as organs at risk (OARs). Twenty-two patients received radiotherapy on kidney levels, 17 on lung levels, and 3 on both levels. _Results:_ All Erasmus-iCycle plans were clinically acceptable. When compared to manual plans, planning target volume (PTV) coverage of auto plans was significantly better. The Homogeneity Index did not differ significantly between the groups. Mean dose to OARs was lower in auto plans concerning both kidneys and the left lung. One hotspot (>110% of D50%) occurred in the spinal cord of one auto plan (33.2 Gy, D50%: 30 Gy). Treatment time was 7% longer in auto plans. _Conclusions:_ Erasmus-iCycle plans showed better target coverage and sparing of OARs at the expense of minimally longer treatment times (for which no constraint was set)

Individualized automated planning for dose bath reduction in robotic radiosurgery for benign tumors

Object To explore the use of automated planning in robotic radiosurgery of benign vestibular schwannoma (VS) tumors for dose reduction outside the planning target volume (PTV) to potentially reduce risk of secondary tumor induction. Methods A system for automated planning (AUTOplans) for VS patients was set up. The goal of AUTO- planning was to reduce the dose bath, including the occurrence of high dose spikes leaking from the PTV into normal tissues, without worsening PTV coverage, OAR doses, or treatment time. For 20 VS patients treated with 1x12 Gy, the AUTOplan was compared with the plan generated with conventional, manual trial-and-error planning (MANplan). Results With equal PTV coverage, AUTOplans showed clinically negligible differences with MANplans in OAR sparing (largest mean difference for all OARs: ΔD2% = 0.2 Gy). AUTOplan dose distributions were more compact: mean/maximum reductions of 23.6/53.8% and 9.6/ 28.5% in patient volumes receiving more than 1 or 6 Gy, respectively (p<0.001). AUTOplans also showed smaller dose spikes with mean/maximum reductions of 22.8/37.2% and 14.2/ 40.4% in D2% for shells at 1 and 7 cm distance from the PTV, respectively (p<0.001). Conclusion Automated planning for benign VS tumors highly outperformed manual planning with respect to the dose bath outside the PTV, without deteriorating PTV coverage or OAR sparing, or significantly increasing treatment time