Goal: To develop a cardiovascular virtual population using statistical modeling and computational biomechanics. Methods: 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 in silico clinical trials. Results: 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. Conclusions: The virtual arterial geometries are efficiently matched to the generated clinical data, both increasing and complementing the variability of the virtual population.

中文翻译：

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一种为支架设计的计算机临床试验生成人类冠状动脉虚拟种群的新方法

目标：使用统计建模和计算生物力学开发心血管虚拟人群。方法：实施临床数据增强算法以使用真实临床数据集有效地生成虚拟临床数据。动脉粥样硬化斑块生长模型用于 3D 重建冠状动脉段，以生成虚拟冠状动脉几何形状（几何数据）。最后，虚拟临床和几何数据的组合是使用一种方法实现的，该方法允许生成可用于计算机临床试验。结果：结果表明，真实和虚拟临床数据之间的一致性很好，平均 gof 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 10,000 名患者。结论：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可变性。