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Juan Carlos del Álamo de Pedro


Juan Carlos del Alamo de Pedro - University of California San Diego, USA

Juan C. del Alamo is a Professor at the Deparment of Mechanical and Aerospace Engineering in the University of California San Diego. He received BS and MS degrees in Aerospace Engineering, and a PhD in computational fluid dynamics at Universidad Politecnica de Madrid. He was a Fulbright postdoctoral fellow at Harvard and at UC San Diego, where he received training in experimental cell mechanics and cardiovascular flows. Prof. del Alamo joined UC San Diego as faculty in 2008 and has hold visiting and adjoint positions at the National Yang Ming University in Taiwan, San Diego State University, and Hospital General Universitario Gregorio Marañon. Prof. del Alamo’s research focuses on biological fluid mechanics, cellular locomotion, traction force microscopy and the non-invasive characterization of cardiac flows. His research has been recognized with a US Geological Survey Director’s Award, the NSF CAREER Award, the Hellman Family Fellowship, and the William Parmley Award from the American College of Cardiology.



Atrial fibrillation (AF) is the most common form of arrhythmia. Compared to the general population, patients with AF have five times the risk of stroke, which can cause major morbidity and death. Anticoagulants may be administered to decrease this risk in selected patients but this treatment carries major associated risks such as internal hemorrhaging. Thus, there is a need for accurate patient selection criteria for anticoagulation treatment. The  goal of this project is to develop patient-specific thrombosis risk scores by analyzing blood flow in the left atrium. We will use each patient’s anatomy obtained from medical imaging to calculate the residence time of blood in the left atrium via computational fluid dynamics. Our rationale is that thromboembolic events have been tightly linked to blood stasis, which can be identified by regions of high blood residence time. The outcome of this collaboration will be a risk score that can be calculated from standard medical images, such as cardiac CT scans and echocardiograms. Such tools could transform clinical decisions affecting millions of patients at risk of stroke.

Imagen Cátedras de Excelencia 2014