GATE data for simulating Y-90 Microsphere Clusters in Human Phantom in Vereos Ring Scanner.Copy

Liver cancer treatment, especially for metastatic cases, poses significant challenges in accurately targeting tumours while sparing healthy tissue. Radioembolisation with yttrium-90 (Y-90) microspheres is a promising technique, but precise imaging of microsphere distribution is crucial. This study utilises T-PEPT, a novel Positron Emission Particle Tracking (PEPT) algorithm that combines topological data analysis with machine learning to identify Y-90 microsphere clusters in a digital twin of a patient's liver. GATE (Geant4 Application for Tomographic Emission) Monte Carlo simulations were utilised to model the radioembolisation procedure, including a detailed human-like phantom and the Philips Vereos PET/CT scanner. T-PEPT demonstrates effective identification of microsphere clusters amidst significant noise, achieving high spatial and temporal resolution. The results suggest that T-PEPT could enable near real-time imaging, enhance dosimetry accuracy, and optimise clinical resource utilisation. Future work incorporating Time-of-Flight (ToF) information and improving detector sensitivity is anticipated to further improve this technique's viability for medical applications.