Fernández-Tena Ana, Arnedo Carlos, Houzeaux Guillaume, Eguzkitza Beatriz
Instituto Nacional de Silicosis, GRUBIPU-ISPA y Facultad de Enfermería, Universidad de Oviedo, Oviedo, España.
Barcelona Supercomputing Center, Department Computer Applications in Science and Engineering, Barcelona, España.
Open Respir Arch. 2024 Dec 12;6(Suppl 2):100394. doi: 10.1016/j.opresp.2024.100394. eCollection 2024 Oct.
The development of lung digital twins (DTs) represents a significant advance in personalized medicine, providing a virtual framework that replicates the structure, function, and pathology of the respiratory system in an individualized manner. DTs integrate clinical data, high-resolution images, and mathematical models to simulate respiratory mechanics, gas diffusion, and fluid dynamics in real time. This technology improves diagnosis, treatment planning, and disease progression monitoring. One of the key applications of lung DTs is the ability to simulate patient-specific response to treatments and predict outcomes, allowing for personalized therapies. Despite advances, the implementation of DTs in clinical practice faces challenges related to data integration, computational efficiency, and ethical considerations regarding data privacy. Nevertheless, lung DTs offer clear promise for improving precision medicine, optimizing patient care, and improving clinical outcomes.
肺数字孪生体（DTs）的发展代表了个性化医疗的重大进步，提供了一个以个性化方式复制呼吸系统结构、功能和病理学的虚拟框架。DTs整合临床数据、高分辨率图像和数学模型，以实时模拟呼吸力学、气体扩散和流体动力学。这项技术改善了诊断、治疗规划和疾病进展监测。肺DTs的关键应用之一是能够模拟患者对治疗的特定反应并预测结果，从而实现个性化治疗。尽管取得了进展，但DTs在临床实践中的实施面临着与数据整合、计算效率以及数据隐私的伦理考量相关的挑战。尽管如此，肺DTs为改善精准医疗、优化患者护理和改善临床结果带来了明确的希望。
