Predictive computational framework to provide a digital twin for personalized cardiovascular medicine

In percutaneous coronary intervention (PCI), the ability to predict post-PCI fractional flow reserve (FFR) and stented vessel informs procedural planning. However, highly precise and effective methods to quantitatively simulate coronary intervention are lacking. This study developed and validated a virtual coronary intervention (VCI) technique for non-invasive physiological and anatomical assessment of PCI. In this study, patients with substantial lesions (pre-PCI CT-FFR of less than 0.80) were enrolled. VCI framework was used to predict vessel reshape and post-PCI CT-FFR. The accuracy of predicted post-VCI CT-FFR, luminal cross-sectional area (CSA) and centreline curvature was validated with post-PCI computed tomography (CT) angiography datasets. Overall, 30 patients are initially screened; 21 meet the inclusion criteria, and 9 patients (9 vessels) are included in the final analysis. The average PCI-simulation time is 24.92 ± 1.00 s on a single processor. The calculated post-PCI CT-FFR is 0.92 ± 0.09, whereas the predicted post-VCI CT-FFR is 0.90 ± 0.08 (mean difference: −0.02 ± 0.05 FFR units; limits of agreement: −0.08 to 0.05). Morphologically, the predicted CSA is 16.36 ± 4.41 mm² and the post-CSA is 17.91 ± 4.84 mm² (mean difference: −1.55 ± 1.89 mm²; limits of agreement: −5.22 to 2.12). The predicted centreline curvature across the stented segment (including ~2 mm proximal and distal margins) is 0.15 ± 0.04 mm⁻¹, while the post-PCI centreline curvature is 0.17 ± 0.03 mm⁻¹ (mean difference: −0.02 ± 0.06 mm⁻¹; limits of agreement: −0.12 to 0.09). The proposed VCI technique achieves non-invasive pre-procedural anatomical and physiological assessment of coronary intervention. The proposed model has the potential to optimize PCI pre-procedural planning and improve the safety and efficiency of PCI. This study aimed to help doctors plan heart procedures more accurately. A common treatment is insertion of a stent, which is a small, mesh-like tube that is inserted into a blood vessel to keep it open. A computer simulation tool that can predict how a patient's heart artery will look and function after a stent is placed was developed. It was tested using scan data from patients and found that it could closely match real post-treatment results. The tool was fast, taking under 30 s to run, and was able to model both blood flow and artery shape. These findings suggest that this method could improve how doctors plan treatments for blocked heart arteries, making procedures safer and more effective. In the future, it may help personalize care and reduce unnecessary risks during heart interventions. Lyu et al. develop a patient-specific virtual coronary intervention (VCI) framework that enables real-time, non-invasive simulation of percutaneous coronary intervention (PCI). This technique accurately predicts post-PCI physiology and vessel morphology, offering a promising tool for optimizing pre-procedural planning and enhancing PCI outcomes.