Publications by authors named "G Benecchi"
Purpose: To train and validate KB prediction models by merging a large multi-institutional cohort of whole breast irradiation (WBI) plans using tangential fields.
Methods: Ten institutions (INST1-INST10, 1481 patients) developed their KB-institutional models for left/right WBI (ten models for right and eight models for left). The transferability of models among centers was assessed based on the overlap of the geometric Principal Component (PC1) of each model when applied to other institutions and/or on the presence of significantly different optimization policies.
Article Synopsis
- * A total of 16 new patients were analyzed to assess the variability in predicted dose-volume-histograms (DVH) for the heart and lungs, finding low inter-institutional variability with standard deviations of 1.8% for the ipsilateral lung and 1.6% for the heart.
- * The results indicated that the KB models were highly transferable with minimal differences, suggesting the potential for developing standard benchmark models for improving treatment consistency in TF-WBI.
Purpose: To quantify inter-institute variability of Knowledge-Based (KB) models for right breast cancer patients treated with tangential fields whole breast irradiation (WBI).
Materials And Methods: Ten institutions set KB models by using RapidPlan (Varian Inc.), following previously shared methodologies.
In craniospinal irradiation, field matching is very sensitive to intrafraction positional uncertainties in cranio-caudal direction, which could lead to severe overdoses/underdoses inside the planning target volume. During the last decade, significant efforts were made to develop volumetric-modulated arc therapy strategies, which were less sensitive to setup uncertainties. In this study, a treatment planning system-integrated method, named automatic feathering (AF) algorithm, was compared against other volumetric-modulated arc therapy strategies.
View Article and Find Full Text PDFAim: To synthesize and characterize the performances of a new all-inorganic nanocomposite (NC) for self-lighted photodynamic therapy against cancer. This NC could allow radiotherapy doses to be reduced, as it enhances the effects of x-rays, generating cytotoxic reactive oxygen species as singlet oxygen.
Materials & Methods: The proposed NC combines CeF and ZnO; CeF absorbs 6-MeV x-rays and activates the photosensitizer ZnO.