915 W State St
Associate Professor, School of Health Sciences
Areas of Expertise
- 1. Developing magnetic resonance imaging and spectroscopy technology for early detection of human cancer treatment responses using in vivo biomarkers.
- 2. Bacteria-based cancer therapy and imaging for rapid tumor tissue destruction in animal tumor models.
School of Health Sciences Research Area(s)
- Imaging Sciences
- Medical Physics
Dr. Qiuhong He has earned her PhD in physical chemistry in the University of North Carolina at Chapel Hill, focusing on novel electrophoretic nuclear magnetic resonance (NMR) technology. She received postdoctoral training at Princeton University, and subsequently joined in vivo NMR division in the Department of Radiology at the Johns Hopkins University School of Medicine. In Princeton, Dr. He has carried out the intermolecular multiple-quantum coherence transfer (iMQC) experiments and observed a novel NMR phenomenon of long-range spin dipolar interactions in solution NMR. In the Johns Hopkins University School of Medicine, Dr. He initiated the development of in vivo magnetic resonance spectroscopic imaging (MRSI) techniques for metabolite detection in tissues containing high concentration of mobile lipids using a mammary mouse tumor model. As a faculty member, she is developing fast MRSI techniques for early detection of human cancer treatment responses (with several patents). Her recent invention of pi-MRSI techniques may help detect prognostic markers of immunotherapy in cancer patients, detect early treatment response in cancer therapy, and differentiate pseudo-progression from true tumor progression in cancer patients under treatment. In addition, her laboratory has generated genetically engineered anti-cancer bacteria that amplify only in tumor tissues. These theranostic agents carry anti-cancer proteins and MR and optical imaging markers. Dr. He will employ these anti-cancer bacteria to enhance immunotherapy using mouse animal models, monitored by MRI or optical imaging. In a collaboration project, machine-learning algorithms are developed for imaging analysis to characterize the bacteria-based cancer treatment effect.
- PhD, 1990, University of North Carolina at Chapel Hill
- Postdoctoral training, 1992, Princeton University.
- Postdoctoral fellow and Research Associate, 1995, the Johns Hopkins University School of Medicine.
- B.S., 1984, Jilin University, China.
Diversity, Equity and Inclusion
- DEI training in the national Nucleate program, 2022 RTP cohort, NC
- Distinguished manuscript reviewer for Magnetic Resonance in Medicine - 2013
- Member, the International Society for Magnetic Resonance in Medicine (ISMRM)
- Active Member, American Association for Cancer Research (AACR)