Dr. Borrego earned his Ph.D. in biomedical engineering with a concentration in medical physics from the University of Florida, Gainesville. He joined the Radiation Epidemiology Branch in 2016 as a postdoctoral fellow and became a research fellow and an independent research scholar in 2019. Dr. Borrego’s research focuses on quantifying the radiation exposure to both patients and staff from medical imaging. His work and contributions to the field have been recognized by several awards, including the DCEG Fellowship Achievement award, DCEG Intramural Research Award, NCI Director’s Award for Population Science, and inaugural selection to the Independent Research Scholar Program of the NIH Office of Intramural Research.
Dr. Borrego’s research focuses on improving our understanding of ionizing radiation, associated health risks, and the development of models to clarify how ionizing radiation, like medical x-rays from radiography and fluoroscopy, deposits energy in the tissues of the human body. He is addressing concerns about fluoroscopically guided intervention (FGI) procedures by developing models of exposure assessment that consider demographic and procedural information, literature-reported radiation exposure data, and physical measurements of x-ray tube output. These data are then used in Monte Carlo simulations of radiation transport coupled with computational models of the human anatomy to estimate the radiation dose in organs and radiosensitive tissues. This work may 1) improve future epidemiological studies of radiogenic risks and 2) inform interventional cardiologists in strategizing and implementing changes in imaging techniques to reduce radiation risks without compromising medical benefits.
Dr. Borrego conducted the largest study in the U.S. on occupational doses and trends over time for medical staff assisting or performing FGI procedures. This study has revealed the importance of compliance and accurate badge placement, to reduce uncertainties in exposure assessment. Currently, he is leading an effort to use readings from personal monitoring devices and Monte Carlo methods to better inform the exposure assessment in large cohorts of occupationally exposed workers, such as the U.S. Radiologic Technologists Study.