A Novel Approach to Generate a Virtual Population of Human Coronary Arteries for In Silico Clinical Trials of Stent Design

Dimitrios Pleouras,Antonis Sakellarios,George Rigas,Georgia S. Karanasiou,Panagiota Tsompou,Gianna Karanasiou,Vassiliki Kigka,Savvas Kyriakidis,Vasileios Pezoulas, George Gois,Nikolaos Tachos,Aidonis Ramos,Gualtiero Pelosi,Silvia Rocchiccioli,Lampros Michalis,Dimitrios I. Fotiadis

IEEE Open Journal of Engineering in Medicine and Biology（2021）

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Abstract

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.

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Key words

Cardiovascular virtual population,clinical data augmentation,plaque growth modeling,in-silico clinical trials

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