Research
INTERESTS
Modeling of regulation in cardiovascular and pulmonary systems
Differential equations and dynamical systems
Data-driven patient-specific parameterization
Numerical methods and optimization in physiological systems
Algorithm development for biomedical applications
Computational fluid dynamics
ONGOING PROJECTS (current collaboration opportunities marked by 
)
Interested in the Systems Modeling and Analysis PhD program? Apply by Feb. 1 for the following academic year. Admissions are done centrally but you may express interest in particular faculty or projects.
Evaluation of Factors in Compromised Breathing in Preterm Infants using Pulmonary Dynamics Modeling
Henry Rozycki MD; Joseph E. Khoury, MD; Russell Moore, MD; Matthew Brandes, PhD (MCV).
Bradford Smith, PhD (CU-Anschutz).
Students: Richard Foster, Jeffrey Evans, Lauren Linkous
- Non-invasive ventilation is increasingly used for respiratory support in preterm infants, and
is associated with a lower risk of chronic lung disease. However, this mode is often not successful
in the extremely preterm infant in part due to the highly compliant (floppy) chest wall at this stage of gestation. A foundational model parameterized for an idealized preterm infant was developed to show the effect of high chest wall compliance on progressive lung volume loss. The first manuscript of this project was published in 2018. - We recently developed a submodel of ribcage / abdominal mechanics to model thoracoabdominal asynchrony, or TAA (also called “chest retractions”). This manuscript was accepted for publication in AJP – Lung Cellular and Molecular Physiology in June 2023!
- We have preliminary sensitivity analysis results and are interested in estimating parameter values related to factors of comprised breathing for either the basic or the TAA models described below. We are currently searching for a data set of spontaneously breathing preterm infants with or without CPAP for parameter estimation of either model.
- Possible additional opportunities include:
- Incorporation of neural control as driver of model
- Addition of gas transport and chemoreflex response to breathing alterations
- Model effects of high frequency oscillation ventilation and/or high flow nasal cannula
- Addition of stochastic components
Modeling Cerebrovascular Reactivity in a Computer Model of Cardiorespiratory Dynamics
Student: Mariana Fernandes Gragnani
- Cardiovascular disease and impaired cerebrovascular reactivity is often associated with impaired regulatory processes, but their interaction is not well understood. The goal of this project is to create a computer model of blood vessel resistance in the brain (cerebrovascular resistance, or CVR) that functionally depends on blood gas levels and blood pressure. This is an extension of published work from 2013 in which an empirical piecewise model of CVR was created within an existing closed-loop compartment model of the whole body circulatory system. Current efforts focus on developing an open-loop models dependent on blood pressure and gas levels based on previously published studies, and incorporate within the closed-loop whole body circulation model framework.
- This model is parameterized with continuous blood pressure, middle cerebral artery blood flow velocity, and expiratory CO2. This data is widely available for adults and we aim to incorporate such data in future studies to compare dynamics between groups of interest.
Mathematical Modeling of Fluid Dynamics in an ECMO Oxygenator
Oliver Karam, MD/PhD (Yale University)
- Extracorporeal Membrane Oxygenation (ECMO) is a life-saving procedure providing cardiac and respiratory support to patients with severe and potentially fatal heart or lung conditions. However, the possibility of clot formation within the oxygenator, a crucial component of the ECMO system, remains a significant concern. We are beginning to explore the development of a mathematical model of the fluid dynamics in an ECMO oxygenator to eventually predict personalized clotting risk in patients.
Designing a Novel Hypothalamic-Pituitary-Adrenal Axis Sensor System and Mathematical Modeling for Clinical Applications.
Benjamin Nicholson MD, David Chan, Vamsi Yadavalli (VCU)
Student: Helen Harris
- The overall project goal is to develop a novel artificial adrenal system that incorporates a multi-analyte sensor system, a mathematical model for interpreting these hormones, and a hormone augmentation system to evaluate four hormones (cortisol, adrenocorticotropic hormone, epinephrine, and norepinephrine) during acute shock.
Collaborative Research: A National Consortium for Synergistic Undergraduate Mathematics via Multi-Institutional Interdisciplinary Teaching Partnerships.
Multiple institutions. Rebecca Segal, Vennie Filippas, Hilary Clark (VCU).
- The overall project goal is to develop sustainable inter-institutional and inter-departmental collaborations that lead to improved outcomes in student transfer of knowledge from Mathematics to the partner discipline. Primary focus is on introductory Differential Equations.
Evaluation of Wall Shear Stress for Investigation of Restenosis in Stented Coronary Arteries Reconstructed Using Optical Coherence.
John F. LaDisa, Jr., Marquette University; Hiromasa Otake MD, Kobe University Graduate School.
Students: Ali Aleiou, Joshua Hughey
- The success of drug eluting stents is limited by restenosis and late stent thrombosis. Stenting as a common intervention alters artery geometry, exposing an artery to adverse wall shear stress (WSS). For DES it is not conclusively known if optimizing WSS leads to clinical benefits. The objective of this study is to determine the relationship between DES-induced WSS indices and two markers of poor outcomes, change in lumen area and category of stent malapposition.
PAST PROJECTS
Fluid dynamics analysis of pulmonary vasculature for understanding pulmonary arterial hypertension.
Mette Olufsen, NCSU; Umar Qureshi (postdoc), NCSU; Naomi Chesler, UC-Irvine; Nick Hill, University of Glasgow.
Student: Mitchel Colebank
Translating Near Infrared Spectrocopy Oxygen Saturation Data for the Noninvasive Prediction of Spatial and Temporal Hemodynamics during Exercise.
John F. LaDisa, Jr., Sheila Schindler-Ivens, and Michael Danduran, Marquette University; Margaret Samyn, Children’s Hospital of Wisconsin.
Image-based Quantification Workflow for Coronary Morphology.
John F. LaDisa, Jr., Marquette University; Raymond Migrino, VA Health Care System (Phoenix); David Marks, Medical College of Wisconsin.
Modeling Autoregulation in the Kidney.
Anita Layton, Duke; Julia Arciero, IUPUI; Ashlee Ford Versypt,
Cardiovascular and Respiratory Regulation, Modeling and Parameter Estimation. PhD Thesis.
Advisor: Mette Olufsen, NCSU.