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核医学中的数字孪生:分子放射治疗中剂量测定方案优化的模块化流程建议。

Digital twins in nuclear medicine: A proposition of a modular pipeline for dosimetry protocol optimization in molecular radiotherapy.

作者信息

Sinsoilliez N, Magnier B, Piron B, Bardiès M, Janaqi S, Boudousq V

机构信息

EuroMov - Digital Health in Motion, IMT - MINES ALES, Université de Montpellier, France.

Institut de Recherche en Cancérologie de Montpellier (IRCM), Équipe Labellisée Ligue Contre le Cancer, INSERM U1194, Université de Montpellier, Institut régional du Cancer de Montpellier (ICM), Montpellier, France.

出版信息

Comput Struct Biotechnol J. 2025 Aug 27;28:306-311. doi: 10.1016/j.csbj.2025.08.027. eCollection 2025.

Abstract

Digital twins (DTs) are emerging tools for simulating and optimizing therapeutic protocols in personalized nuclear medicine. In this paper, we present a modular pipeline for constructing patient-specific DTs aimed at assessing and improving dosimetry protocols in PRRT such as therapy. The pipeline integrates three components: (i) an anatomical DT, generated by registering patient CT scans with an anthropomorphic model; (ii) a functional DT, based on a physiologically-based pharmacokinetic (PBPK) model created in SimBiology; and (iii) a virtual clinical trial module using GATE to simulate particle transport, image simulation, and absorbed dose distribution. Validation metrics include SSIM and DICE for registration quality, and MSE for PBPK model fitting with clinical quantification data. The anatomical DT module has been successfully implemented and validated on clinical data, demonstrating its ability to generate realistic, patient-morphed phantom for image-based dosimetry. The modular design allows for individual validation and reuse of each component, enabling stepwise development and integration. This architecture offers a strong foundation for evaluating dosimetry protocols and allowing multi-center standardization efforts in the future. This pipeline introduces a modular and adaptable DT framework to support protocol optimization in radionuclide therapy. As validation progresses, it holds strong potential for future use as a predictive tool for absorbed dose estimation prior to therapy, enabling safer and more effective personalized treatment planning.

摘要

数字孪生(DTs)是用于在个性化核医学中模拟和优化治疗方案的新兴工具。在本文中,我们提出了一种模块化流程,用于构建针对患者的数字孪生,旨在评估和改进肽受体放射性核素治疗(PRRT)等治疗中的剂量测定方案。该流程集成了三个组件:(i)通过将患者CT扫描与拟人模型配准生成的解剖学数字孪生;(ii)基于在SimBiology中创建的基于生理的药代动力学(PBPK)模型的功能数字孪生;以及(iii)使用GATE模拟粒子传输、图像模拟和吸收剂量分布的虚拟临床试验模块。验证指标包括用于配准质量的结构相似性指数(SSIM)和骰子系数(DICE),以及用于PBPK模型与临床定量数据拟合的均方误差(MSE)。解剖学数字孪生模块已在临床数据上成功实施和验证,证明了其为基于图像的剂量测定生成逼真的、符合患者形态的体模的能力。模块化设计允许对每个组件进行单独验证和重用,实现逐步开发和集成。这种架构为评估剂量测定方案和未来的多中心标准化工作提供了坚实的基础。该流程引入了一个模块化且适应性强的数字孪生框架,以支持放射性核素治疗中的方案优化。随着验证工作的推进,它在未来作为治疗前吸收剂量估计的预测工具具有很大潜力,能够实现更安全、更有效的个性化治疗规划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdd8/12415080/36cd31683f3f/gr001.jpg

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