Purpose: To develop an auto-planning strategy for right-sided breast treatments by adapting the deep learning-based predicted dose from a pre-existing left-sided breast model.
Methods: The procedure was executed in RayStation v12A TPS and applied to early breast cancer treatments delivering 48Gy/42.4Gy in 16 fractions for PTVBoost and PTVBreast, respectively. Initially, the predicted dose...
Purpose: To develop a fast, deep-learning based Monte Carlo dose distributions (MCDD) denoising framework for 6, 10 and 15 MV volumetric modulated arc therapy (DeepSMCP) and integrate it into the Swiss Monte Carlo Plan (SMCP).
Methods: DeepSMCP is integrated into the SMCP framework as an additional dose-calculation algorithm and can be selected using the SMCP’s graphical user...
Purpose
The objective of this study is to assess the feasibility of automated O-Ring Halcyon Linac SBRT plans for lung metastases and determine a Planning Target Volume (PTV) threshold as an indicator of plan quality. The study also contrasts plan quality and treatment durations between Halcyon Linac (HAL) and CyberKnife (CK) robotic SBRT.
Methods
A total of 17 previously treated CK lung...
Purpose: The selection of the collimator angle for linac-based stereotactic radiosurgery (SRS) of multiple brain metastases (BMs) is important to reduce the bridge dose in between the different lesions and minimize brain toxicities. In this work, we developed an algorithm which simultaneously optimizes the dose distribution and the collimator angle for SRS of multiple BMs.
Methods:...
Purpose: Research treatment planning systems (TPS) are needed for further development of optimization algorithms and exploration of novel concepts not supported by commercial TPS. However, research TPS are not approved medical products and lack the rigorous testing of commercial TPS. In this work, we developed a tool to upload treatment plans generated with our in-house TPS into the...
Purpose
The aim of this project is to verify the entire treatment quality of Ethos (Varian, Pola Alto, USA) online adaptive radiotherapy (oART).
Methods
An end-to-end test, specifically designed for oART, was conducted with a water-equivalent 3D printed pelvis phantom. Five organs were included in this phantom: bladder, prostate, rectum and femoral heads. The organs were modeled...
Purpose:
Daily adaptive proton therapy (DAPT) differs significantly from established processes in conventional radiotherapy. Online adaptation is technologically challenging, needs to be fast and automated and involves new, non-routine steps (e.g., daily plan re-optimization). Therefore, a tailored design of the DAPT workflow, including QA procedures, is required to ensure its safe clinical...
