Mathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins
Abstract
This article presents the general framework of theranostic digital twins (TDTs) in computational nuclear medicine, designed to support clinical decision-making and improve cancer patient prognosis through personalized radiopharmaceutical therapies (RPTs). It outlines potential clinical applications of TDTs and proposes a roadmap for successful implementation. Additionally, the chapter provides a conceptual overview of the current state of the art in the mathematical and computational modeling of RPTs, highlighting key challenges and the strategies being pursued to address them.
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