Forum for Applied Imaging Research (FAIR): Breast Imaging
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Video Conference To
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Molecularly Targeted Characterization of Breast Cancer Using Dedicated Breast PET Imaging
Dr. Natsuko Onishi is an Assistant Professional Researcher in the Department of Radiology and Biomedical Imaging at UCSF and the Associate Director of Translational Research in the Breast Imaging Research Program (BIRP). She earned her MD from Kyoto University in 2006 and is a Japanese board-certified radiologist. While practicing clinically, Dr. Onishi pursued advanced research in breast MRI, earning her PhD in Biomedical Imaging and Technology from Kyoto University Graduate School of Medicine in 2017. She continued her postdoctoral training in breast imaging at Memorial Sloan Kettering Cancer Center before joining BIRP at UCSF in 2019.
At UCSF, Dr. Onishi has focused on developing quantitative breast MRI biomarkers using extensive MRI datasets from the multi-center neoadjuvant breast cancer clinical trial I-SPY 2. Since 2022, her research has expanded to include dedicated breast PET (dbPET) imaging for evaluating primary breast cancer response to neoadjuvant therapy. As PI of dbPET projects, Dr. Onishi strives to advance imaging biomarkers that enhance clinical decision-making in breast cancer care by integrating MRI and dbPET technologies.
Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation
Maggie Chung, MD is an Assistant Professor in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco, specializing in breast imaging. She earned her medical degree from the Warren Alpert Medical School of Brown University, completed her internship at Scripps Mercy Hospital in San Diego, and completed both her diagnostic radiology residency and breast imaging fellowship at UCSF. During residency, she received the Elmer Ng Outstanding Resident Award, the Margulis Society Resident Research Award, and the RSNA Roentgen Resident/Fellow Research Award.
Her research is supported by the National Institutes of Health, Breast Cancer Research Foundation, and Radiological Society of North America. Dr. Chung’s research focuses on the development and clinical translation of artificial intelligence tools for breast imaging. Her work spans simulated contrast-enhanced breast MRI using deep learning, breast cancer risk prediction models for personalized screening, and the use of risk models to support expedited mammogram assessment.
Dr. Chung is a member of the Science and Technology Resource Group within UCSF’s Center for Intelligent Imaging (ci²) and UCSF Clinical Trials Committee. She has served on the UCSF Radiology Residency Admissions Committee, the Quality Assurance Committee and as a UCSF representative to the California Radiological Society.
UCSF Radiology and Biomedical Imaging
AI for Personalized Care
Dr. Adam Yala is an assistant professor of Computational Precision Health, Statistics and Computer Science at UC Berkeley and UCSF, and the Founder & CEO of Voio. His academic research focuses on developing machine learning methods for personalized health care and translating them into clinical care. His previous research focused on two areas: 1) predicting future cancer risk, and 2) designing personalized screening policies. His breast cancer tool, Mirai, has been tested at 66 hospitals from 30 countries. Adam's tools now underly prospective trials, and his research has been featured in the Washington Post, New York Times, and the Boston Globe. Adam obtained his BS, MEng and PhD in Computer Science from MIT where he was a member of MIT Jameel Clinic and MIT CSAIL.