David Izquierdo-Garcia

David Izquierdo is an Assitant Professor in Radiology in the Department of Radiology at Massachusetts General Hospital / Harvard Medical School with interest in improving non-invasive molecular imaging quantification with combined PET/MRI scanners. In particular most of Dr. Izquierdo’s research is applied to brain and cardiovascular imaging to provide useful diagnostic tools for early detection of cardiovascular disease and brain disorders.

Since Dr. Izquierdo’s initial steps in medical imaging at the University of Cambridge, UK, he has been working on improving PET image quantification, mostly using MR-based techniques. Among them, Ihe implemented for the first time a partial volume effect correction method for cardiovascular imaging. Dr. Izquierdo has also focused on improving simultaneous PET/MR image quantification by applying MR-based attenuation correction (AC) for PET imaging. Currently more than a dozen international groups have implemented this method for brain AC. Dr. Izquierdo is currently involved in a novel line of research using artificial intelligence on cardiovascular applications, that aims to provide improved cardiac motion detection and quantification.

Education

• Doctor of Philosophy (Ph.D.) Université Bordeaux I (2000 — 2004)
• Master's Degree Université Bordeaux I (2000 — 2000)
• Engineer's Degree Universidad de Zaragoza (1995 — 2000)

Select Publications

1. Izquierdo-Garcia D, Davies JR, Graves MJ, Rudd JH, Gillard JH, Weissberg PL, Fryer TD, Warburton EA. Comparison of methods for magnetic resonance-guided [18-F]fluorodeoxyglucose positron emission tomography in human carotid arteries: reproducibility, partial volume correction, and correlation between methods. Stroke. 2009 Jan;40(1):86-93.

2. Izquierdo-Garcia D, Hansen AE, Förster S, Benoit D, Schachoff S, Fürst S, Chen KT, Chonde DB, Catana C. An SPM8-based approach for attenuation correction combining segmentation and nonrigid template formation: application to simultaneous PET/MR brain imaging. J Nucl Med. 2014 Nov;55(11):1825-30.

3. Morales M*, Izquierdo-Garcia D*, Aganj I, Kalpathy-Cramer J, Rosen BR, Catana C. Implementation and Validation of a 3D Cardiac Motion Estimation Network (CarMEN). Radiology: Artificial Intelligence. In press. 2019.