A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases.

Introduction: This study aims to apply a conditional Generative Adversarial Network (cGAN) to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance (MR) images of the thorax.

Methods: Sixty patients treated for lung lesions were enrolled and divided into training (32), validation (8), internal (10,T) and external (10,T) test set.

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

Background: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment planning workflow. Time-consuming and inter-observer variability are main issues in manual OAR delineation, mainly in the head and neck (H & N) district. Deep-learning based auto-segmentation is a promising strategy to improve OARs contouring in radiotherapy departments.

Dosimetric Impact of Inter-Fraction Variability in the Treatment of Breast Cancer: Towards New Criteria to Evaluate the Appropriateness of Online Adaptive Radiotherapy.

Purpose: As a discipline in its infancy, online adaptive RT (ART) needs new ontologies and criteria to evaluate the appropriateness of its use in clinical practice. In this experience, we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to identify in advance the treatment fractions where patients might benefit from an online ART approach.

Methods: The study was focused on right breast cancer patients treated using standard adjuvant RT on an artificial intelligence (AI)-based linear accelerator.

Five-Fraction Stereotactic Radiotherapy for Brain Metastases: A Single-Institution Experience on Different Dose Schedules.

Introduction: The most common intracranial neoplasm diagnosed in adults are brain metastases (BrM). The benefit in terms of clinical control and toxicity for stereotactic radiotherapy (SRT) has been investigated for patients with low load of BrM.

Aim: The aim of this single-institution experience was to investigate the best dose schedule for five-fraction SRT (FFSRT).

Radiofrequency Thermoablation and Hypofractionated Radiotherapy Combined Treatment for Bone Metastases: A Retrospective Study.

Introduction: Bone metastases (BMs) are the common cause of cancer-related pain, as approximately 45% of cancer patients suffer from bone pain (BP). Radiotherapy (RT) is well established as BP treatment strategy; also, other approaches have been shown to be effective in this setting. Radiofrequency thermoablation (RFA) in a combined strategy with RT appears to be feasible and effective in the treatment of metastatic BP ensuring a better quality of life.