Purpose: One of the recent methods to improve the efficiency, consistency and overall plan quality in radiotherapy is to use dose prediction. Based on prior experience of similar cases, deep neural networks can predict an achievable dose for a specific case. Instead of planning purposes, we are exploring the possibilities of using dose prediction in the QA of automatic segmentation. For...
Introduction
Phantoms for quality assurance (QA) of deep hyperthermia therapy (DHT) devices are not commercially available. In this work, we suggest an easy to build phantom to perform commissioning and regular QA on the performance of DHT phased-array devices.
Methods
The phantom container consists of a 64cm long polyurethane tube with an external diameter of 25cm and a wall thickness of...
Purpose: To study the influence of objective functions and weights, as well as mean doses to secondary organs at risk (OAR) on Pareto front robustness.
Methods: We wrote and validated a python script that controls RayStation (RaySearch) treatment planning system (TPS) and calculates Pareto fronts. Then, we randomly chose thirty-one prostate cancer patients treated at our clinic and...
