Pleouras Dimitrios, Sakellarios Antonis, Rigas George, Karanasiou Georgia S, Tsompou Panagiota, Karanasiou Gianna, Kigka Vassiliki, Kyriakidis Savvas, Pezoulas Vasileios, Gois George, Tachos Nikolaos, Ramos Aidonis, Pelosi Gualtiero, Rocchiccioli Silvia, Michalis Lampros, Fotiadis Dimitrios I
Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece.
Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece.
IEEE Open J Eng Med Biol. 2021 May 20;2:201-209. doi: 10.1109/OJEMB.2021.3082328. eCollection 2021.
To develop a cardiovascular virtual population using statistical modeling and computational biomechanics. A clinical data augmentation algorithm is implemented to efficiently generate virtual clinical data using a real clinical dataset. An atherosclerotic plaque growth model is employed to 3D reconstructed coronary arterial segments to generate virtual coronary arterial geometries (geometrical data). Last, the combination of the virtual clinical and geometrical data is achieved using a methodology that allows for the generation of a realistic virtual population which can be used in clinical trials. The results show good agreement between real and virtual clinical data presenting a mean gof 0.1 ± 0.08. 400 virtual coronary arteries were generated, while the final virtual population includes 10,000 patients. The virtual arterial geometries are efficiently matched to the generated clinical data, both increasing and complementing the variability of the virtual population.
利用统计建模和计算生物力学开发心血管虚拟人群。实施一种临床数据增强算法，以使用真实临床数据集高效生成虚拟临床数据。采用动脉粥样硬化斑块生长模型对冠状动脉节段进行三维重建，以生成虚拟冠状动脉几何形状（几何数据）。最后，使用一种方法将虚拟临床数据和几何数据相结合，从而生成可用于临床试验的逼真虚拟人群。结果显示，真实临床数据与虚拟临床数据之间具有良好的一致性，平均g值为0.1±0.08。生成了400条虚拟冠状动脉，而最终的虚拟人群包括10000名患者。虚拟动脉几何形状与生成的临床数据有效匹配，增加并补充了虚拟人群的变异性。
