The project will be conducted in the Department of Information & Communication Technologies of the Universitat Pompeu Fabra, Barcelona, Spain for the computational part (supervised by ICREA Research Prof. B. Bijnens and Dr. Oscar Camara) and in the The Fetal Medicine Research Centre, at the Maternity Hospital of Hospital Clínic (supervised by Dr F. Crispi, Dr. E. Eixarch and Prof E. Gratacos). Other (international) collaborators will be involved, depending on the project.
PhD project 1: Development of a multi-scale model of the cardiovascular system of a foetus with aortic coarctation
Congenital Heart Disease (CHD) is one of the major determinants of perinatal deaths. The origin and the structural and hemodynamic remodelling caused by CHD are not fully understood. Computational models have shown to be a great approach to better understand the underlying mechanisms of different cardiovascular diseases and to perform patient-specific simulations to understand remodelling and test different treatment strategies and therapies. Aortic coarctation is one of the most difficult cardiac defects to diagnose before birth, and it accounts for 8% of congenital heart diseases. This congenital disease consists on the narrowing of the distal aortic arch in mild cases, thus reducing the blood flow in the fetal aortic arch. Antenatal diagnosis is crucial for early treatment of the neonate and to decrease the risk of morbidity and mortality.
Therefore, the aim of this project is the development of a multi-scale model of the cardiovascular system of a fetus with aortic coarctation (and related defects such as ventricular or atrial septal defects), including also the implementation of a tissue growth model to be able to assess the cardiac growth and remodelling during development. It will consist on a 0D model of the circulation, including all the relevant vessels and vascular beds, potentially coupled to a simple 3D model of the fetal heart. Then, a simplified mathematical model of cardiac growth and remodelling will be incorporated in order to study the effects of hemodynamic and mechanical alterations under aortic coarctation into cardiac development. In our research group, we have started an implementation of a model of the aortic coarctation using CellML, coupled with OpenCOR [1,2]. Within this project, this model will be further developed to include the heart and growth and remodelling models. Ultrasonographic data from patients with aortic coarctation will be used to validate the model. The results raised from this project will provide insights into cardiac remodelling and the pathophysiological processes involved in CHD.
 Garcia-Canadilla P, Crispi F, Cruz-Lemini M, Triunfo S, Nadal A, Valenzuela-Alcaraz B, Rudenick PA, Gratacos E, Bijnens BH. Patient-specific estimates of vascular and placental properties in growth-restricted fetuses based on a model of the fetal circulation. Placenta. 2015;36:981-989.
 Giménez Mínguez P, Bijnens B, Bernardino G, Lluch E, Soveral I, Gómez O, Garcia- Canadilla P. Assessment of haemodynamic remodeling in fetal aortic coarctation using a lumped model of the circulation. In: Pop M, Wright GA, editors. Functional Imaging and Modelling of the Heart. 9th International Conference, FIMH 2017, Proceedings. 2017 Jun 11-13; Toronto, Canada. p. 471-80
PhD project 2: The Heart-Brain axis, or There and Back again: the journey towards brain development traverses vascular territories
The heart and the brain are arguably the two most fascinating and important organs of the human body. Scientists have been studying these organs for centuries but mainly at an individual organ level. There is a need for a more systemic approach to study the physiology of some neurological and cardiovascular processes that remain not well understood, even with the current deluge of medical data and advanced computational tools available nowadays. A good example involves brain development, especially in abnormal conditions such as after insults during pregnancy (Intra-Uterine Growth Restriction, IUGR). There are plain and numerous evidences on the effect of IUGR on the cardiovascular system and in the brain of these infants, but they have never been studied together. The aim of this project is to create a computational modelling platform, linking heart and brain systems, to test the influence of mechanical forces originating from vascular anatomy, haemodynamics and metabolic characteristics on brain development in normal and abnormal conditions. This research will open up opportunities for understanding systems-based mechanisms of other conditions affecting heart and brain such as congenital heart disease, schizophrenia, autism, neurodegenerative diseases or neurocardiology applications.
The first task will then involve the development of a model of neurological development coupling brain mechanics (Fig. 1) with a multi-scale model of blood circulation and metabolism. It will create a multi-system, -physics and -scale model of brain development, including the influence of mechanical forces, haemodynamics and metabolic characteristics. Local forces will arise from anisotropic tissue surrounded by fluid and skull as well as pulsatile forces through vessels and their acute and chronic remodelling. Blood circulation models from heart to brain will provide regional flow and pressures at different scales, whereas metabolic exchange models will be included to describe oxygen and nutrients diffusion from vasculature to brain tissue. In a second phase of the project, parametric studies will be performed to identify the most relevant characteristics for normal and abnormal brain development. Robust verification and validation experiments of the developed computational models will be implemented, both for each subsystem individually and globally. A thorough sensitivity analysis of the parameters will be achieved to determine the ones having the largest influence on brain development and how cardiovascular deficiencies can induce abnormal neurodevelopment.
This project is strongly interdisciplinary, joining clinical, biomedical and technical expertise. The PhD candidate will be surrounded by a team including experts, postdocs and junior researchers from different disciplines (engineering/physics, biomedical/experimental), available in the hosting research group (PhySense, part of the BCN-MedTech research unit at UPF) and from our collaborators (P. Saez, Universitat Politècnica de Catalunya; D. Rueckert, Imperial College London; M. Sermesant, M. Lorenzi, Inria, France; O. Coulon, Aix-Marseille Université; Dr. F. Crispi, Dr. E. Eixarch, Hospital Clínic de Barcelona; M. Vázquez, Barcelona Supercomputing Centre; V. Borrell, Instituto Neurociencias Alicante).
Profiles of the candidates and contact information:
We are looking for highly motivated young researchers with a Master degree (or equivalent) in Biomedical Engineering, Physics, Mechanical Engineering, Applied Mathematics, Computational Science, or related disciplines, willing to study and do research at the leading edge of biomedical engineering. Interest in biomedical and clinical applications is essential. Experience with computer sciences and having proven programming skills would be of importance. Candidates have excellent teamwork and communication skills and are enthusiastic about collaborating with a diverse range of international partners. We expect them to be fluent in English as this will be the language used to interrelate with the different partners.
Female applicants are explicitly encouraged to apply and will be treated preferentially whenever they are equally qualified as other male candidates.
On the basis of this project, a training plan will be set up by selecting the best training opportunities in the PhD programme of UPF and available initiatives within our collaborators. Clinical training will be organized depending on the needs and background of the researcher. The biomedical engineering groups of the UPF, included in the Research Unit BCN-MedTech, focus on integrating engineering/physics with physiology, working closely together with academic clinical centres. Therefore, the groups provide methodologies and offers support for clinical and basic researchers to help to define the research approach from the basic understanding of the disease towards the clinical study; to select/design the appropriate investigational tools to assess the relevant clinical parameters; to quantify the diagnostic information (from clinical information to imaging data) to extract the most pertinent information; and to interpret the results and relate them to the pathophysiological knowledge.