T32 Presentations: Drs. Andrew Callen and Geraldine Tran
Date
Type
Time Duration
Location
Notes
Broadcasts to:
China Basin, Large Classroom
Mt. Zion, 1600 Divisadero Street, C250
Mission Bay Hospital, 1975 4th Street, C1719
VAMC Bldg 200 Room 2A-147
ZSFG, Radiology, Minagi Library
Connect via Zoom: https://zoom.us/j/9055865224
Speakers
The Department of Radiology and Biomedical Imaging has a long record of excellence in clinical and academic radiology, and has one of the largest research enterprises funded through intra- and extramural funding and private donors. With numerous outstanding basic scientists and clinicians engaged in innovative imaging research across five principal campus units, the department provides a fertile ground for interdisciplinary collaboration. The T32 program exists to jumpstart the academic careers of junior radiologists and nuclear medicine physicians and to provide the essential foundation for developing a research program as an independent investigator.
Lecture Title: 'The Emerging Neuroimaging Profile of the HIV-Infected, Virally Suppressed Individual'
Andrew Callen, MD received his medical degree from UC San Diego. His diagnostic radiology residency at UCSF will be completed in June 2019. He served as a T32 fellow in 2018-2019. Dr. Callen’s research focus involves using perfusion and vascular imaging techniques including phase contrast/arterial spin labeling MRI, cerebrovascular reactivity and arterial wall imaging to interrogate the pathophysiology of the vasculopathy behind chronic HIV infection. Dr. Callen will continue his training at UCSF as a Neuroradiology fellow in July 2019.
Lecture Title: 'New Applications of Breast MRI During Neoadjuvant Therapy'
Geraldine Tran is a T32 Research Scholar in the UCSF Department of Radiology and Biomedical Imaging. She also attended UCSF for medical school and her prelim-intern year. She is starting as a first year radiology resident at Boston University in July. As a 2018-2019 NIH T-32 scholar, Geraldine's research focused on using breast MRI for predicting breast cancer outcomes.