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Mathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins.

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PET clinics 2026 Vol.21(1) p. 117-131
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출처

Ryhiner M, Song Y, Saboury B, Glatting G, Rahmim A, Shi K

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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 thr

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APA Ryhiner M, Song Y, et al. (2026). Mathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins.. PET clinics, 21(1), 117-131. https://doi.org/10.1016/j.cpet.2025.09.005
MLA Ryhiner M, et al.. "Mathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins.." PET clinics, vol. 21, no. 1, 2026, pp. 117-131.
PMID 41162315

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 article 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.

MeSH Terms

Humans; Radiopharmaceuticals; Neoplasms; Nuclear Medicine; Precision Medicine