Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma.

Purpose: Complexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of non-coplanar treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated beam angle optimization was used to define non-coplanar VMAT class solutions (CSs), each consisting of a coplanar arc and additional 1 or 2 fixed, non-coplanar partial arcs.

Methods: Automated planning was used to generate a coplanar VMAT plan with 5 complementary computer-optimized non-coplanar IMRT beams (VMAT+5) for each of the 20 included patients.

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.

Pre-clinical validation of a novel system for fully-automated treatment planning.

Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to 'manual' trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs).

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.

Currently, radiation-oncologists generally evaluate a single treatment plan for each patient that is possibly adapted by the planner prior to final approval. There is no systematic exploration of patient-specific trade-offs between planning aims, using a set of treatment plans with a-priori defined (slightly) different balances. To this purpose, we developed an automated workflow and explored its use for prostate cancer.

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer.

In this study we developed a workflow for fully-automated generation of deliverable IMRT plans for a 1.5 T MR-Linac (MRL) based on contoured CT scans, and we evaluated automated MRL planning for rectal cancer. The Monte Carlo dose calculation engine used in the clinical MRL TPS (Monaco, Elekta AB, Stockholm, Sweden), suited for high accuracy dose calculations in a 1.

Texture analysis of 3D dose distributions for predictive modelling of toxicity rates in radiotherapy.

Background And Purpose: To explore the use of texture analysis (TA) features of patients' 3D dose distributions to improve prediction modelling of treatment complication rates in prostate cancer radiotherapy.

Material And Methods: Late toxicity scores, dose distributions, and non-treatment related (NTR) predictors for late toxicity, such as age and baseline symptoms, of 351 patients of the hypofractionation arm of the HYPRO randomized trial were used in this study. Apart from DVH parameters, also TA features of rectum and bladder 3D dose distributions were used for predictive modelling of gastrointestinal (GI) and genitourinary (GU) toxicities.

Late toxicity in the randomized multicenter HYPRO trial for prostate cancer analyzed with automated treatment planning.

Purpose/objective: Assess to what extent the use of automated treatment planning would have reduced organ-at-risk dose delivery observed in the randomized HYPRO trial for prostate cancer, and estimate related toxicity reductions. Investigate to what extent improved plan quality for hypofractionation scheme as achieved with automated planning can potentially reduce observed enhanced toxicity for the investigated hypofractionation scheme to levels observed for conventional fractionation scheme.

Material/methods: For 725 trial patients, VMAT plans were generated with an algorithm for automated multi-criterial plan generation (autoVMAT).

The impact of treatment accuracy on proton therapy patient selection for oropharyngeal cancer patients.

Background And Purpose: The impact of treatment accuracy on NTCP-based patient selection for proton therapy is currently unknown. This study investigates this impact for oropharyngeal cancer patients.

Materials And Methods: Data of 78 patients was used to automatically generate treatment plans for a simultaneously integrated boost prescribing 70 Gy/54.

Impact of model and dose uncertainty on model-based selection of oropharyngeal cancer patients for proton therapy.

Background: Proton therapy is becoming increasingly available, so it is important to apply objective and individualized patient selection to identify those who are expected to benefit most from proton therapy compared to conventional intensity modulated radiation therapy (IMRT). Comparative treatment planning using normal tissue complication probability (NTCP) evaluation has recently been proposed. This work investigates the impact of NTCP model and dose uncertainties on model-based patient selection.