Bart Bijnens obtained an MSc in Electronic Engineering and PhD in Medical Sciences (1997, KULeuven, Belgium). He was tenured Professor of Cardiovascular Imaging&Dynamics at the Medical Faculty in Leuven (1998-04), supervised clinical research at St. George's Hospital in London (2005-6) and was resident Visiting Professor at the University of Zagreb (2007), Croatia. Since Sept. 2008, he is ICREA Research Professor in Barcelona, first at the UPF and currently at IDIBAPS, leading the 'Translational Computing in Cardiology' group. He is recognised as international expert in pathophysiological concepts and (image-based) assessment of CV diseases, with a reputation of being able to explain basic pathophysiology principles and put technical developments in context. This resulted in many international collaborations/publications/lectures as well as being requested by centres all over the world for advice on research in cardiovascular mechanics and imaging.
Translational Cardiovascular Pathophysiology, focussing on assessing cardiac function and understanding changes induced by disease and how treatment can modulate this remodelling. This is approached by integrating information handling and computing, combined with basic pathophysiology knowledge in order to advance clinical sciences. This implies an approach from basic understanding of disease towards a clinical study; selecting/designing appropriate investigational tools to assess relevant clinical parameters; quantifying diagnostic information (from clinical information to imaging data) to extract pertinent information and interpreting results and relate them to pathophysiology. Recent projects include the combination of computational modelling with interpretable machine learning in order to find easy to implement/deploy techniques for the identification of patients at risk for adverse events, as well as to improve our understanding of disease and decission making.
- Garcia-Canadilla P, Mohun TJ, Bijnens B & Cook AC 2022, 'Detailed quantification of cardiac ventricular myocardial architecture in the embryonic and fetal mouse heart by application of structure tensor analysis to high resolution episcopic microscopic data', Frontiers In Cell And Developmental Biology, 10:1000684.
- Dejea H, Schlepütz CM, Méndez-Carmona N, Arnold M, Garcia-Canadilla P, Longnus S, Stampanoni M, Bijnens B & Bonnin A 2022, 'A tomographic microscopy-compatible Langendorff system for the dynamic structural characterization of the cardiac cycle', Frontiers in Cardiovascular Medicine, 9:1023483.
- Evangelista A, Pineda V, Guala A, Bijnens B, Cuellar H, Rudenick P, Sao-Aviles A, Ruiz A, Teixido-Tura G, Rodriguez-Lecoq R, Bellmunt S, Ferreira I & Rodríguez-Palomares J 2022, 'False lumen flow assessment by magnetic resonance imaging and long-term outcomes in uncomplicated aortic dissection', Journal of the American College of Cardiology, 79(24), 2415-2427.
- Garcia-Canadilla P, Sanchez-Martinez S, Martí-Castellote PM, Slorach C, Hui W, Piella G, Aguado AM, Nogueira M, Mertens L, Bijnens BH & Friedberg MK 2022, 'Machine-learning–based exploration to identify remodeling patterns associated with death or heart-transplant in pediatric-dilated cardiomyopathy', The Journal of Heart and Lung Transplantation, 41(4):516-526.
- Sanchez-Martinez S, Camara O, Piella G, Cikes M, Gonzalez-Ballester MA, Miron M, Vellido A, Gomez E, Fraser AG & Bijnens B 2022, 'Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging', Frontiers In Cardiovascular Medicine, 8:765693.
- Adão R & Bijnens B 2022, 'At the heart of artificial intelligence: the future might well be based on synthetic cells', Cardiovascular Research, 118(12):e82–e84.