Forum for Applied Imaging Research (FAIR): Brain Tumor
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Forum for Applied Imaging Research (FAIR) is presented by the UCSF Radiology and Biomedical Imaging's Seminar and Presentation Committee
4431 America/Los_Angeles public Add to CalendarForum for Applied Imaging Research (FAIR) is presented by the UCSF Radiology and Biomedical Imaging's Seminar and Presentation Committee
Speakers
Preclinical Studies
Dr. Pavithra Viswanath is an Associate Professor in the Department of Radiology and Biomedical Imaging at UCSF. She graduated with a Ph D in Biochemistry from the Indian Institute of Science in Bangalore, India. The overall vision of her research is to harness insights from tumor genetics, epigenetics, and biology to drive the preclinical development of novel, metabolic imaging biomarkers that will ultimately benefit patients by enabling the non-invasive assessment of tumor burden and response to therapy. In parallel, she will pinpoint metabolic vulnerabilities in the tumor and immune microenvironment that can be exploited for the development of novel therapeutic agents. Her long-term vision is to develop an integrated, clinically translatable metabolic therapy and imaging strategy for patients battling cancer.
Multimodal Modeling
Dr. Lin is an Assistant Professor in Residence at the UCSF Department of Radiation Oncology. She went to the Special Class for the Gifted Young at Xi’an Jiaotong University and received her bachelor’s degree in Nuclear Science and Engineering, before starting her Ph.D. in Nuclear Engineering at Rensselaer Polytechnic Institute. During this time, her research focused on exploring advanced computational technologies to advance medical physics, including GPU computing, machine learning and computational human phantom development. She completed her three-year therapeutic medical physics residency at University of Pennsylvania and was the Chief Resident in her final year. During her time at UPenn, her research focused on Artificial Intelligence-based cardiac substructures auto segmentation and Machine Learning-based tumor motion prediction, and the projects were awarded internal and vendor grants during her residency. Her research interests range from AI-based automated segmentation, predictive multi-omics modeling and data-driven automation of clinical processes.
AI in Brain Tumors
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. More
Moderator
After Dr. Adam Autry obtained his PhD in Bioengineering from the Joint Graduate Program at UC Berkeley/UCSF, under the mentorship of Sarah J Nelson, he joined the Li Lab to continue research characterizing molecular markers of malignant brain tumors. His current work focuses on real-time imaging of in vivo metabolism in adults with infiltrating gliomas using the technique of hyperpolarized carbon-13 (HP-13C) MRI, which probes glycolytic and oxidative phosphorylation pathways by means of injectable tracers whose magnetization has been transiently enhanced via specialized instrumentation. As part of this effort, he has pursued optimizing HP-13C data acquisition methods involving atlas-based prescriptions for serial imaging studies and investigated features of aberrant metabolism in progressive glioma based on the modeling of [1-13C] pyruvate kinetics.