Janine Lupo, PhD, is a Professor in the Surbeck Laboratory of Advanced Imaging and Neuroimaging Research Interest Group of the Department of Radiology and Biomedical Imaging. She is a member of the UCSF/UC Berkeley Graduate Group in Bioengineering, Helen Diller Family Comprehensive Cancer Center, Institute for Computational Health Sciences, and Quantitative Biosciences Institute. Dr. Lupo received her BSE in Bioengineering at the University of Pennsylvania, School of Engineering and Applied Science in Philadelphia before completing her PhD at the UCSF/UCB PhD Joint Graduate Group in Bioengineering. Before accepting an in residence position, Dr. Lupo was an Assistant and Associate Researcher in the Department of Radiology and Biomedical Imaging at UCSF.
Dr. Lupo’s research focuses on the development and application of novel MR imaging data acquisition, processing, and analysis techniques for the evaluation of patients with brain tumors and other neurological diseases using our research 3T and 7T whole body scanners. This includes the development of quantitative algorithms critical for processing data from advanced acquisitions for patient studies, implementation of statistical and machine learning models to relate imaging markers with biological characteristics from pathology and clinical outcome in order to both identify patients who would benefit most for a given therapy, and monitor the effects of therapy over time on tumor control, normal brain tissue structure, and cognition.
Dr. Lupo has been the Principal or Co-Principal Investigator for multiple NIH and DoD grants, as well as a co-Project leader of 2 projects within an NIH Programmatic Project Grant and Brain Tumor SPORE Grant. She has published over 75 research articles.
Expertise:
Bioengineering
Specialty:
Neuroimaging
Professional Interests:
Magnetic resonance imaging, ultra-high field MRI, algorithm development for quantitative image analysis, imaging biomarker discovery, brain cancer, neurological diseases, evaluation of therapy, the effects of therapy on cognition, statistical modeling, and deep learning
