Purpose: The formulation and optimization of radiation therapy plans are complex and time-
consuming processes that heavily rely on the expertise of medical physicists. Consequently …

Background and purpose To investigate the performance of head-and-neck (HN) organs-at-
risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep …

Purpose Adaptive stereotactic body radiation therapy (SBRT) for prostate cancer (PC) by the
1.5 T MR-linac currently requires online planning by an expert user. A fully automated and …

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

Background This study aimed to evaluate an a-priori multicriteria plan optimization algorithm
(mCycle) for locally advanced breast cancer radiation therapy (RT) by comparing …

Aim In this study, a not yet commercially available fully-automated lexicographic optimization
(LO) planning algorithm, called mCycle (Elekta AB, Stockholm, Sweden), was validated for …

Purpose We previously developed a virtual treatment planner (VTP), an artificial intelligence
robot, operating a treatment planning system (TPS). Using deep reinforcement learning …

Purpose To investigate and report on the diffusion and clinical use of automated
radiotherapy planning systems in Italy and to assess the perspectives of the community of …

Purpose To investigate the performance of 4 atlas-based (multi-ABAS) and 2 deep learning
(DL) solutions for head-and-neck (HN) elective nodes (CTVn) automatic segmentation (AS) …

Aim To validate a fully-automated lexicographic optimization-planning system (mCycle,
Elekta) for single-(SL) and multiple-(ML, up to 4 metastases) lesions in intracranial …