个性化手术时代的数字孪生体。

Digital twins for the era of personalized surgery.

作者信息

Mekki Yosra Magdi, Luijten Gijs, Hagert Elisabet, Belkhair Sirajeddin, Varghese Chris, Qadir Junaid, Solaiman Barry, Bilal Muhammad, Dhanda Jaghtar, Egger Jan, Deng Jun, Khanduja Vikas, Frangi Alejandro F, Zughaier Susu M, Stotland Mitchell A

机构信息

College of Medicine, Qatar University, QU Health, Doha, Qatar.

Institute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital (AöR), Essen, Germany.

出版信息

NPJ Digit Med. 2025 May 15;8(1):283. doi: 10.1038/s41746-025-01575-5.

DOI:10.1038/s41746-025-01575-5

PMID:40374901

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12081715/

Abstract

Digital twins can aid surgeons in training and in performing interventions with greater awareness and precision. The range and variety of digital twins in surgery are described, and their use across perioperative care is discussed. While largely experimental, they are beginning to show promise for the enhancement of personalized, adaptive, and data-driven surgical care. Issues relevant to the greater adoption and deployment of digital twins are all considered.

摘要

数字孪生可以帮助外科医生进行训练，并在实施干预时提高认知度和精准度。本文描述了手术中数字孪生的范围和种类，并讨论了它们在围手术期护理中的应用。虽然目前大多仍处于实验阶段，但它们已开始展现出提升个性化、适应性和数据驱动型手术护理的潜力。文中还考虑了与数字孪生更广泛采用和部署相关的问题。