Speaker
Description
Artificial Intelligence (AI) is increasingly integrated into medical physics, offering powerful tools for enhancing treatment planning. In Boron Neutron Capture Therapy (BNCT), a promising radiotherapy that selectively targets tumors using boron-containing drugs and neutron irradiation, AI can support precise treatment. My work presents a novel Treatment Planning System (TPS), IT_STARTS, applied for BNCT in Glioblastoma Multiforme (GBM) patients, integrating the application of Convolutional Neural Networks for Deep Learning-based CT segmentation. A key innovation is the implementation of an automated and analytical approach to patient positioning, a crucial issue in BNCT, based on dosimetric analysis within the GTV and OAR, enabling accurate, reproducible setups and direct comparison between AI-generated and manual contours. The goal is to maximize dose delivered in the tumor while sparing healthy tissues, simplifying the planning process and ensuring consistent, reproducible results. The proposed AI-supported TPS represents a step forward to more automated, optimized BNCT treatment planning.
