T-32 Presentations (Day 1): Biomedical Imaging for Clinician Scientists
Date
Type
Time Duration
Location
Notes
*Broadcasting lecture to the following sites:
China Basin (350)
Mission Bay (C-1719)
Mt.Zion (C-250)
VAMC (2A-147)
ZSFGH (1x57)
Speakers
The goal of the T32 program is to train a new generation of leaders in academic radiology with expertise in biomedical imaging research by providing a facilitated transition between residency/fellowship and academic faculty positions in Radiology & Biomedical Imaging. These individuals will play a major role in maximizing the healthcare benefits that will flow from interdisciplinary translational research linking advances in the sciences of genomics, proteomics and bioinformatics with continual technological evolution in biomedical imaging. We believe that UCSF is ideally positioned to train these future leaders, because it provides the critical combination of exceptional residents and faculty in an environment of excellent funding, established interdisciplinary cooperation, and outstanding institutional and departmental resources.
Javier Villanueva-Meyer is a PGY-5 resident in the Department of Radiology and Biomedical Imaging. As a 2015-2016 NIH T-32 scholar, Dr. Villanueva-Meyer's research investigations have focused on PET imaging of infection using metabolic labeling of the bacterial cell wall with the goal of developing a non-invasive strategy to detect infection in vivo. Dr. Villanueva-Meyer will complete his UCSF Diagnostic Radiology Residency in June 2016, and will continue his training at UCSF with a fellowship in Neuroradiology.
Lecture Title - "PET imaging of infection using metabolic labeling of the bacterial cell wall"
Vignesh Arasu is a PGY5 resident in the Department of Radiology and Biomedical Imaging. He received his Medical Degree from UCSF, and has been performing breast imaging research with Nola Hylton, PhD and Bonnie Joe, MD, PhD for the last 6 years. He will continue as a Breast Imaging/Abdominal Imaging fellow at UCSF for 2016-2017.
Lecture Title: "Predicting Breast Cancer Response to Neoadjuvant Chemotherapy using MRI Background Parenchymal Enhancement"