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

Per-fraction planning to enhance optimization degrees of freedom compared to the conventional single-plan approach

Objective. In conventional radiotherapy, a single treatment plan is generated pre-treatment, and delivered in daily fractions. In this study, we propose to generate different treatment plans for all fractions (‘Per-fraction’ planning) to reduce cumulative organs at risk (OAR) doses. Per-fraction planning was compared to the ‘Conventional’ single-plan approach for non-coplanar 4 × 9.5 Gy prostate stereotactic body radiation therapy (SBRT). Approach. An in-house application for fully automated, non-coplanar multi-criterial treatment planning with integrated beam angle and fluence optimization was used for plan generations. For the Conventional approach, a single 12-beam non-coplanar IMRT plan with individualized beam angles was generated for each of the 20 included patients. In Per-fraction planning, four fraction plans were generated for each patient. For each fraction, a different set of patient-specific 12-beam configurations could be automatically selected. Per-fraction plans were sequentially generated by adding dose to already generated fraction plan(s). For each fraction, the cumulative- and fraction dose were simultaneously optimized, allowing some minor constraint violations in fraction doses, but not in cumulative. Main results. In the Per-fraction approach, on average 32.9 ± 3.1 [29;39] unique beams per patient were used. PTV doses in the separate Per-fraction plans were acceptable and highly similar to those in Conventional plans, while also fulfilling all OAR hard constraints. When comparing total cumulative doses, Per-fraction planning showed improved bladder sparing for all patients with reductions in Dmean of 22.6% (p = 0.0001) and in D1cc of 2.0% (p = 0.0001), reductions in patient volumes receiving 30% and 50% of the prescribed dose of 54.7% and 6.3%, respectively, and a 3.1% lower rectum Dmean (p = 0.007). Rectum D1cc was 4.1% higher (p = 0.0001) and Urethra dose was similar. Significance. In this proof-of-concept paper, Per-fraction planning resulted in several dose improvements in healthy tissues compared to the Conventional single-plan approach, for similar PTV dose. By keeping the number of beams per fraction the same as in Conventional planning, reported dosimetric improvements could be obtained without increase in fraction durations. Further research is needed to explore the full potential of the Per-fraction planning approach.</p

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 145 problems (patients), divided over 7 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. This record is the main landing page for links to the TROTS dataset. Links to the project page, updates and newer versions can be found here, and will be updated if necessary

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

Complementing Prostate SBRT VMAT With a Two-Beam Non-Coplanar IMRT Class Solution to Enhance Rectum and Bladder Sparing With Minimum Increase in Treatment Time

Purpose Enhance rectum and bladder sparing in prostate SBRT with minimum increase in treatment time by complementing dual-arc coplanar VMAT with a two-beam non-coplanar IMRT class solution (CS). Methods For twenty patients, an optimizer for automated multi-criterial planning with integrated beam angle optimization (BAO) was used to generate dual-arc VMAT plans, supplemented with five non-coplanar IMRT beams with individually optimized orientations (VMAT+5). In all plan generations, reduction of high rectum dose had the highest priority after obtaining adequate PTV coverage. A CS with two most preferred directions in VMAT+5 and largest rectum dose reductions compared to dual-arc VMAT was then selected to define VMAT+CS. VMAT+CS was compared with automatically generated i) dual-arc coplanar VMAT plans (VMAT), ii) VMAT+5 plans, and iii) IMRT plans with 30 patient-specific non-coplanar beam orientations (30-NCP). Plans were generated for a 4 x 9.5 Gy fractionation scheme. Differences in PTV doses, healthy tissue sparing, and computation and treatment delivery times were quantified. Results For equal PTV coverage, VMAT+CS, consisting of dual-arc VMAT supplemented with two fixed, non-coplanar IMRT beams with fixed Gantry/Couch angles of 65 degrees/30 degrees and 295 degrees/-30 degrees, significantly reduced OAR doses and the dose bath, compared to dual-arc VMAT. Mean relative differences in rectum D-mean, D-1cc, V-40GyEq and V-60GyEq were 19.4 +/- 10.6%, 4.2 +/- 2.7%, 34.9 +/- 20.3%, and 39.7 +/- 23.2%, respectively (all p Conclusions The proposed two-beam non-coplanar class solution to complement coplanar dual-arc VMAT resulted in substantial plan quality improvements for OARs (especially rectum) and reduced irradiated patient volumes with minor increases in treatment delivery times

MR-Linac Radiotherapy - The Beam Angle Selection Problem

BACKGROUND: With the large-scale introduction of volumetric modulated arc therapy (VMAT), selection of optimal beam angles for coplanar static-beam IMRT has increasingly become obsolete. Due to unavailability of VMAT in current MR-linacs, the problem has re-gained importance. An application for automated IMRT treatment planning with integrated, patient-specific computer-optimization of beam angles (BAO) was used to systematically investigate computer-aided generation of beam angle class solutions (CS) for replacement of computationally expensive patient-specific BAO. Rectal cancer was used as a model case. MATERIALS AND METHODS: 23 patients treated at a Unity MR-linac were included. BAO(x) plans (x=7-12 beams) were generated for all patients. Analyses of BAO(12) plans resulted in CS(x) class solutions. BAO(x) plans, CS(x) plans, and plans with equi-angular setups (EQUI(x), x=9-56) were mutually compared. RESULTS: For x>7, plan quality for CS(x) and BAO(x) was highly similar, while both were superior to EQUI(x). E.g. with CS(9), bowel/bladder D(mean) reduced by 22% [11%, 38%] compared to EQUI(9) (p<0.001). For equal plan quality, the number of EQUI beams had to be doubled compared to BAO and CS. CONCLUSIONS: Computer-generated beam angle CS could replace individualized BAO without loss in plan quality, while reducing planning complexity and calculation times, and resulting in a simpler clinical workflow. CS and BAO largely outperformed equi-angular treatment. With the developed CS, time consuming beam angle re-optimization in daily adaptive MR-linac treatment could be avoided. Further systematic research on computerized development of beam angle class solutions for MR-linac treatment planning is warranted