Analyzing data from patients with pulmonary hypertension (Mette Olufsen)

Prerequisites: Differential equations, interest in biology, programming experience.

Outline: Pulmonary hypertension is a rare but deadly disease, which requires both imaging and invasive measurements to diagnose (1). The disease is often detected late as it shares symptoms with several other diseases, and it is not easy to determine how successful the given treatments are. To do so requires integrating imaging data with dynamic measurements (2).

Research objectives: A validated a fluid mechanics model integrating CT images and dynamic blood pressure measurements from right heart catheterization that can predict the load on the heart at rest & exercise.

Outcomes: Mathematical model integrating imaging data with dynamic measurements; local and global sensitivity analysis determining what model parameters impact predictions of blood pressure and flow at rest and during exercise (5 min walk test); a study of what parameters can be identified given the model and data; and simulations predicting effects of vasodilatory treatment at rest and during exercise.

  • Noordegraaf A, Groeneveldt J, Bogaard H. Pulmonary hypertension. Eurp Resp Rev. 2016;25:4-11.
  • Chambers MJ, Colebank MJ, Qureshi MU, Clipp R, Olufsen MS. Structural and hemodynamic properties of murine pulmonary arterial networks under hypoxia-induced pulmonary hypertension. Proc Inst Mech Eng H. 2020;234:1312-1329.