Lead PI:
Center Researchers:
Collaborating Partners
- Brigham and Women’s Hospital
- UC San Diego
- UC Denver
The Challenge
Cardiovascular diseases, particularly those involving coronary artery obstructions, are a leading cause of morbidity and mortality worldwide. Accurately assessing the severity of these obstructions is crucial for determining appropriate treatment strategies, such as stenting.
Traditionally, the measurement of fractional flow reserve (FFR) has been a critical diagnostic tool for evaluating coronary blockages and ischemic burden. However, FFR measurements require an invasive procedure, in which a pressure wire is inserted into the coronary arteries. This procedure, while informative, carries inherent risks and discomfort for patients.
Moreover, current diagnostic methods often fail to capture the full scope of complex blood flow dynamics, such as vorticity and wall shear stress, which are crucial for assessing patients in the diagnostic “grey zone”—cases where ischemic severity is uncertain and where more nuanced clinical decision-making is required. In many instances, these patients may either undergo unnecessary stenting or fail to receive needed intervention, due to the limited physiological insight provided by traditional diagnostic tools.
To enable a safer, more accurate, and data-rich approach to cardiovascular diagnosis, we have developed an innovative solution.
Our Solution
To overcome these challenges, our research team is advancing the use of digital twin technology in cardiovascular care, leveraging high-performance computing to noninvasively evaluate coronary artery disease.
A key innovation in our approach is the ability to reconstruct high-fidelity 3D vascular geometries from standard 2D coronary angiograms. This advancement overcomes limitations of traditional imaging techniques, ensuring a more complete representation of coronary anatomy, including key side branches that influence blood flow.
To overcome these challenges, our research team is advancing the use of digital twin technology in cardiovascular care, leveraging high-performance computing to noninvasively evaluate coronary artery disease. A key innovation in our approach is the ability to reconstruct high-fidelity 3D vascular geometries from standard 2D coronary angiograms. This advancement overcomes limitations of traditional imaging techniques, ensuring a more complete representation of coronary anatomy, including key side branches that influence blood flow.
These patient-specific 3D models serve as the input to HARVEY, a specialized computational fluid dynamics (CFD) solver that simulates coronary blood flow at micrometer-level resolution. By integrating high-resolution CFD modeling with anatomically accurate 3D reconstructions, our framework enables:
- Noninvasive computation of FFR, providing a safer and more efficient alternative to invasive pressure-wire measurements.
- Simulation of complex hemodynamic phenomarkers, including longitudinal vorticity, velocity, and wall shear stress (WSS), which extend beyond FFR to improve clinical decision-making.
A fully patient-specific evaluation of ischemic burden, ensures that treatment plans are based on a more accurate physiological assessment. Our collaboration with leading institutions such as Brigham and Women’s Hospital, UC San Diego, and UC Denver has helped validate this approach. A recent two-center study demonstrated that HARVEY-derived FFR achieved an area under the curve (AUC) of 0.91 compared to invasive FFR measurements, with a positive predictive value of 90.2% and a negative predictive value of 89.6%. This accuracy, coupled with the ability to predict major adverse cardiac events using longitudinal vorticity as a key biomarker, underscores the power of this approach for risk stratification and decision-making.
Beyond FFR, our digital twin framework provides a comprehensive, patient-specific analysis of cardiovascular function, offering clinicians more precise information to guide treatment decisions. For patients in the diagnostic “grey zone,” where traditional FFR alone may not be sufficient, the ability to assess vorticity and wall shear stress provides deeper insight into the ischemic potential of arterial blockages.
By integrating digital twin technology, high-resolution CFD modeling, and patient-specific 3D vascular reconstructions, we are not only enhancing patient safety by reducing the need for invasive diagnostics but also advancing precision medicine in cardiovascular care. Our research underscores Duke’s commitment to leveraging digital and computational innovations to improve the detection, tracking, and treatment of human diseases.