This study aimed to predict the outcome of patient specific quality assurance (PSQA) in IMRT
for breast cancer using complexity metrics, such as MU factor, MAD, CAS, MCS. Several …

Background and purpose Clinical knowledge-based planning (KBP) models dedicated to
prostate radiotherapy treatment may require periodical updates to remain relevant and to …

Background In radiation oncology, automation of treatment planning has reported the
potential to improve plan quality and increase planning efficiency. We performed a …

Introduction Previous literature has shown general trade-offs between plan complexity and
resulting quality assurance (QA) outcomes. However, existing solutions for controlling this …

Intensity-modulated radiotherapy (IMRT) is one of the main treatments for patients with
cancer, and its treatment planning holds significant importance. Compared to manual …

Purpose Deep learning (DL)-based dose distribution prediction can potentially reduce the
cost of inverse planning process. We developed and introduced a structure-focused loss (L …

The aim of this study was to evaluate knowledge-based treatment planning (KBP) models in
terms of their dosimetry and deliverability and to investigate their clinical benefits. Three …

Purpose To develop an automated planning approach in Raystation and evaluate its
feasibility in multiple clinical application scenarios. Methods An automated planning …

The prediction of an additional space for the dose sparing of organs at risk (OAR) in
radiotherapy is still difficult. In this pursuit, the present study was envisaged to find out the …

Introduction Acquisition of dosimetric knowledge by radiation therapy planners is a
protracted and complex process. This study delves into the impact of empirical predictive …