Speaker
Description
Personalized dosimetry is a fundamental tool in nuclear medicine for monitoring and optimizing treatments with radionuclides. WIDMApp (Wearable Individual Dose Monitoring Application) [Morganti et al. Med. Phys. 2021] is an innovative approach under development to improve dosimetric accuracy by enabling personalized dose assessment during Targeted RadioNuclide Treatments (TRNTs) through real-time dosimetry and deconvolution algorithms.
The WIDMAPP framework integrates a set of wearable sensors specifically developed to monitor the activity in the body. They provide data to an innovative deconvolution algorithm capable of reconstructing Time Activity Curves (TACs) of individual organs involved in radiopharmaceutical biokinetics. TACs reconstruction is based on Monte Carlo (MC) algorithms, personalized by the acquisition of the patient’s anatomic images. The reconstruction of individual TACs for specific organs in the patient’s body allows unprecedented precision in dose evaluation. Hence, WIDMApp allows us to model with high precision the activity distribution in the body and its time evolution, improving all aspects of patient radiation protection.
We present a simulation study based on Geant4 MC simulations, in which TACs obtained as output by the WIDMApp approach have been used to assess radiation exposure to caregivers and clinical staff involved in the patient’s treatment. Anatomical details have been simulated using computational phantoms. The aim of this work is to produce a detailed radiation exposure map around the patient, providing guidance for the radiation protection of caregivers and clinical staff involved in the treatment administration. This is particularly important in scenarios involving patients needing care (e.g., children or non-self-sufficient individuals) where frequent and prolonged proximity is required.