Interdisciplinary Approaches Based on Fluid Dynamics and Data Sciences for Biomedical Application

Dear Colleagues,

Fluid dynamics has become the mainstay of transport phenomena in biomechanics, generating new avenues for the development of technology-enhanced monitoring, as well as therapeutic and diagnostic modalities across various biomedical and healthcare applications. The data obtained from image-based computational and experimental biomedical flows, many of which cannot be assessed through standard clinical measurements, offer new possibilities for visualizing and non-invasively quantifying the pathophysiology of diseases, such as blood flow in the circulatory system, airflow in the respiratory system, interstitial fluid flow, and mass transport in tissues. These capabilities promise to provide key insights into disease progression and subsequent physiological responses, thus aiding in clinical decision-making for various cardiovascular and respiratory diseases. They also enable the objective evaluation of the safety and performance of a broad range of medical devices (artificial valves, vascular stents, circulatory assisting devices) and equipment (ventilators, infusion pumps, blood pressure monitors) integral to clinical practice. This Special Issue of Applied Sciences welcomes the submission of new and innovative research that utilizes fluid dynamics in biomedical applications, with a particular focus on the integration of data-driven approaches and artificial intelligence (AI) methods. The scope of this Special Issue includes, but is not limited to, the following topics:

• Advances in computational methods and experimental techniques for the in silico quantification of 4D velocity, pressure, and shear stress in vessels and airways.
• Coupling strategies for biomedical fluid–structure interaction problems where a biological fluid interacts with tissue (blood/vessel, blood/valve, air/lung, cell/platelet/blood).
• Extracting medically meaningful information from computationally and/or experimentally obtained data for innovative physiological indices and/or biomarkers.
• Individualized virtual treatment planning and outcome prediction, such as thoracic endovascular aortic repair with a stent.
• Advances in drug delivery systems and methods, with a focus on enhancing efficiency and achieving targeted therapeutics.
• Current methods for image-based CFD with medical applications.
• Interdisciplinary approaches that couple fluid dynamics with data science (artificial intelligence, neural networks, and decision trees) for improved prediction, characterization, and decision making.
• The application of image segmentation techniques for the extraction and quantification of anatomical and physiological features in biomedical flows, enabling the enhanced analysis of fluid structure interactions, organ-specific modeling, and personalized healthcare diagnostics. Original work that addresses the latest research and technical developments is encouraged, but review papers and comparative studies are also welcome.

Dr. Philippe Meliga
Prof. Dr. Elie Hachem
Guest Editors

Manuscript Submission Information

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• computational and experimental fluid dynamics
• biomedical flows
• cardiovascular and respiratory diseases
• flow patterns and forces in patient-specific circulatory pathways
• medical imaging
• virtual treatment planning
• drug delivery
• medical imaging
• machine learning methods