Computational methods are emerging as relevant tools for diagnosing, treating, and quantifying disease progression. However, the translation of these computational methods to the clinic is not yet a reality. The BioSiMM Lab focuses on patient-specific multi-scale modeling and computational fluid dynamics. Our goal is to leverage computational simulations to provide improved patient-specific risk-stratification metrics and enable the design of personalized therapies at a reasonable computational cost. The group's research areas include thrombosis, vascular and microvascular blood flow modeling, transport and drug delivery, and medical device development, emphasizing investigating sex differences in cardiovascular disease.
Noelia Grande Gutiérrez joined the Department of Mechanical Engineering at Carnegie Mellon University in Fall 2021. Her research group works at the intersection of computational engineering and medicine. The BioSiMM Lab strives to provide new insight into health and disease towards more personalized patient care using computational modeling.
Computational modeling of thrombosis
As the common underlying process of myocardial infarction, ischemic stroke, and venous thromboembolism, thrombosis is the leading cause of death globally. Despite being the focus of numerous studies, mechanisms driving thrombosis, specifically in disease, are not yet completely understood. Understanding why a blood clot forms under specific flow conditions and how its growth may be affected by hemodynamics, patient-specific coagulation profiles, blood biochemistry, genetics, or other systemic factors is essential to improve patient outcomes. We aim to develop new models that combine a data-driven and a physics-based approach and allow integrating experimental and clinical data into a multi-scale simulation framework.
Patient-specific blood flow simulations: From image data to hemodynamic variables
Computational simulations allow us to augment routine medical image data and obtain functional information on an individual patient basis. Using simulations, we can compute stress on the arterial wall to assess potential wall dysfunction and remodeling or, based on the flow conditions, identify and quantify procoagulant environments to determine the risk of thrombosis. This information is typically unavailable otherwise or requires a highly invasive procedure. In the BioSiMM Lab, we develop and apply multiphysics computational models to provide novel insight into cardiovascular disease and help support clinical decision-making regarding therapy or surgical intervention.
Sex differences in coronary artery disease
The main characteristic of coronary artery disease (CAD) in female patients is a non-obstructive pattern, with microvascular involvement in many cases. The current gold standard for coronary assessment — coronary angiography and fractional flow reserve — targets primarily obstructive CAD. Therefore, the risk of ischemic heart disease in female patients is often underestimated. There is a need for more effective, sex-based, diagnostic approaches for non-obstructive CAD. We aim to extract critical information from image-based, multiphysics computational simulations that would lay the groundwork for developing new risk stratification metrics.
Non-invasive hemodynamic data at a low computational cost
One of the main limitations to adopting computational models for routine clinical use is the high computational cost and long turnaround times. One of the BioSiMM Lab goals is to engineer new modeling approaches that allow obtaining accurate and computationally feasible solutions, facilitating clinical translation. We leverage reduced-order modeling and data-driven solutions towards this goal.
Li Fen Frothingham
N. Grande Gutiérrez, T. Sinno, S.L. Diamond. “A 1D-3D hybrid model of patient-specific coronary hemodynamics.” Cardiovascular Engineering and Technology (2021)
N. Grande Gutiérrez, M. Alber, A.M. Kahn, Jane C. Burns, M. Mathew, Brian W. McCrindle, A.L. Marsden. ”Computational modeling of blood component transport related to coronary artery thrombosis in Kawasaki disease patients.” PLoS computational biology, Vol. 17 (9) (2021)
N. Grande Gutiérrez, K. N. Shankar, T. Sinno, S.L. Diamond. “Thrombosis and Hemodynamics: external and intrathrombus gradients.” Current Opinion in Biomedical Engineering, Vol. 19 (2021)
N. Grande Gutiérrez, A. Kahn, J.C. Burns, A.L. Marsden. “Computational blood flow simulations in Kawasaki disease patients: Insight into coronary artery aneurysm hemodynamics.” Global cardiology science & practice, (3) (2017)
N. Grande Gutiérrez, O. Shirinsky, N.V. Gagarina, G.A. Lyskina, R. Fukazawa, S. Ogawa, J.C. Burns, A.L. Marsden, A.M. Kahn. “Assessment of coronary artery aneurysms caused by Kawasaki disease using transluminal attenuation gradient analysis of computerized tomography angiograms.” American Journal of Cardiology, Vol.120 (4) (2017)