Qun Zhao, Professor of Physics
Our research in the MRI physics lab is centered on one of the most advanced imaging technologies, MRI, and its biomedical applications. Magnetic resonance imaging (MRI) is an imaging technique to produce high quality images of the human/animal body. MRI is based on magnetic resonance of nucleus (e.g. 1H or proton) to obtain chemical and physical information about molecules. In medical practice, MRI is used to distinguish pathological tissue (such as a tumor) from normal tissue. MRI scan is harmless since it uses strong magnetic fields and non-ionizing radiation in the radio frequency range, compared to CT scans and X-rays which involve doses of ionizing radiation. Also, MRI provides a high contrast resolution of the soft tissue.
The research is divided into the following directions:
1. Experimental MR Physics: This research focuses primarily on radio frequency transmit/receive coil design, application of super-paramagnetic iron oxide nano-particles as MRI contrast agent, multinuclear spectroscopy (31P), measurement and correction of magnetic field.
2. Computational MRI Physics: Computational MRI physics is the study and implementation of numerical algorithms in order to solve problems in MRI physics based on a quantitative theory, such as Monte Carlo simulation. In addition, electromagnetic (EM) simulation using finite difference in time domain (FDTD) method is also our research interest.
3. MR applications in biomedicine: MRI has been applied extensively in medical imaging, such as early detection/diagnosis of tumor, human brain imaging (functional MRI), diffusion tensor imaging, etc.
4. Access to the state-of-the-art MRI technology: In my lab, graduate students will have an opportunity to learn how to use the state-of-the-art 3 Tesla magnet (manufactured by General Electric Healthcare) located at the BioImaging Research Center (BIRC) on UGA campus, and perform computational /experimental MR physics research.
Gregory Simchick, Kelly M. Scheulin, Wenwu Sun, Sydney E. Sneed, Madison M. Fagan, Savannah R. Cheek, Franklin D. West & Qun Zhao*. Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI. Scientific Reports volume 11, Article number: 12406 (2021)
Steven Hui, …, Qun Zhao, Xiaopeng Zhouac, Gasper Zupance, Richard A.E. Edden , Shinichiro Luke Nakajima∗ , Shiori Honda. Frequency drift in MR spectroscopy at 3T. Neuroimage. Volume 241, 1 November 2021, 118430
Latchoumane CV, Betancur MI, Simchick GA, Sun MK, Forghani R, Lenear CE, Ahmed A, Mohankumar R, Balaji N, Mason HD, Archer-Hartmann SA, Azadi P, Holmes PV, Zhao Q, Bellamkonda RV, Karumbaiah L. Engineered glycomaterial implants orchestrate large-scale functional repair of brain tissue chronically after severe traumatic brain injury. Sci Adv. 2021 Mar 5;7(10):eabe0207. doi: 10.1126/sciadv.abe0207. PMID: 33674306; PMCID: PMC7935369.
Scheulin KM, Jurgielewicz BJ, Spellicy SE, Waters ES, Baker EW, Kinder HA, Simchick GA, Sneed SE, Grimes JA,Zhao Q, Stice SL, West FD. Exploring the predictive value of lesion topology on motor function outcomes in a porcine ischemic stroke model. Sci Rep. 2021 Feb 15;11(1):3814. doi: 10.1038/s41598-021-83432-5. PMID: 33589720; PMCID: PMC7884696.
Latchoumane, C. -F. V., Betancur, M. I., Simchick, G. A., Sun, M. K., Forghani, R., Lenear, C. E., Ahmed A, Mohankumar R, Balaji N, Mason HD, Archer-Hartmann SA, Azadi P, Holmes PV, Zhao Q, Bellamkonda RV,Karumbaiah, L. (2020). Neurotrophic Factor-Laden Acellular Chondroitin Sulfate Scaffolds Promote Chronic Functional Recovery After Severe Traumatic Brain Injury. BioRxiv. doi:10.1101/2020.06.21.116970
Liu, Z., Simchick, G., Qiao, J., Ashcraft, M., Cui, S., Nagy, T., Zhao, Q., and Xiong, M. Reactive Oxygen Species-Triggered Dissociation of a Polyrotaxane-Based Nanochelator for Enhanced Clearance of Systemic and Hepatic Iron. ACS Nano 2021, 15,1, 419-433. https://doi.org/10.1021/acsnano.0c01083
Fang X, Sun W, Jeon J, Azain M, Kinder H, Ahn J, Chung H, Mote R, Filipov N, Zhao Q, Rayalam, S, Park H . Perinatal Docosahexaenoic Acid Supplementation Improves Cognition and Alters Brain Functional Organization in Piglets. Nutrients. 2020;12(7):E2090. Published 2020 Jul 15. doi: 10.3390/nu12072090
Gregory Simchick, Alice Shen, Brandon Campbell, Hea Jin Park, Franklin D. West, and Qun Zhao*. Pig Brains Have Homologous Resting-State Networks with Human Brains. Brain Connectivity. 2019, 9(7): 566-579. DOI: 10.1089/brain.2019.0673
Logun, M., Wynens, K., Simchick, G., Zhao, W., Mao, L., Zhao, Q., Mukherjee, S., Brat, D., Karumbaiah, L., “Surfen-Mediated Blockade of Extratumoral Chondroitin Sulfate Glycosaminoglycans Inhibits Glioblastoma Invasion”. The FASEB Journal. Published Online: 9 Aug 2019 doi.org/10.1096/fj.201802610RR
Journal Articles and Book Chapters
44. Hui-Ju Young, Nathan T. Jenkins, Qun Zhao, Kevin K. McCully. A Comparison between Muscle Echo Intensity and Percent Intramuscular Fat Measured with High Resolution T1-weighted MRI. Muscle and Nerve. 2015.
43. Wang L., Potter W. M. and . In vivo quantification of SPIO nanoparticles for cell labeling based on MR phase gradient images, Contrast Media Mol. Imaging, 10, pages 43-50, 2015.
42. Lee, J., Cardenas-Rodriguez, J., Pagel, M., Platt, M., Kent, M., . Comparison of analytical and numerical analysis of the reference region model for DCE-MRI. Magnetic Resonance Imaging. Volume 32, Issue 7, September 2014, Pages 845-853.
41. Xin Zhang, Xiang Li, Changfeng Jin, Hanbo Chen, Kaiming Li, Dajiang Zhu, Xi Jiang, Tuo Zhang, Jinglei Lv, Xintao Hu, Junwei Han, Qun Zhao, Lei Guo, Lingjiang Li, Tianming Liu. Identifying and Characterizing Resting State Networks in Temporally Dynamic Functional Connectomes. Brain Topography. November 2014, Volume 27, Issue 6, pp 747-765
40. Luning Wang, Wei Tang, Jin Xie, . Improving detection specificity of iron oxide nanoparticles (IONPs) using the SWIFT sequence with long T2 suppression. Magnetic Resonance Imaging. Volume 32, Issue 6, July 2014, Pages 671-678.
39. Wei Tang, Zipeng Zhen, Ce Yang, Luning Wang, Taku Cowger, Hongmin Chen, Trever Todd, Khan Hekmatyar, Qun Zhao, Yanglong Hou,* and Jin Xie*. Fe5C2 Nanoparticles with High MRI Contrast Enhancement for Tumor Imaging. Small. Article first published online: 18 DEC 2013. Volume 10, Issue 7, pages 1245 -1249, April 9, 2014,
38. Xin Zhang, Lei Guo, Xiang Li, Tuo Zhang, Dajiang Zhu, Kaiming Li, Hanbo Chen, Jinglei Lv, Changfeng Jin, Qun Zhao, Lingjiang Li, Tianming Liu.Characterization of Task-free and Task-performance Brain States via Functional Connectome Patterns. Medical Image Analysis Volume 17, Issue 8, December 2013, Pages 1106 - 1122.
37. William Potter, Luning Wang, Kevin McCully, and . Evaluation of a New 1H/31P Dual-Tuned Birdcage Coil for 31P Spectroscopy" Concepts in Magnetic Resonance Part B Volume 43, Issue 3, pages 90 - 99, August 2013
36. Luning Wang, Curtis A. Corum, Djaudat Idiyatullin, Michael Garwood, and . "T1 Estimation for Aqueous Iron Oxide Nanoparticle Suspensions Using a Variable Flip Angle SWIFT Sequence". Magnetic Resonance in Medicine. 2013 Aug;70(2):341-7. doi: 10.1002/mrm.24831. Epub 2013 Jun 28.
35. Wei Tang, Zipeng Zhen, Ce Yang, Luning Wang, Taku Cowger, Hongmin Chen, Trever Todd, Khan Hekmatyar, Qun Zhao, Yanglong Hou,* and Jin Xie* "Fe5C2 Nanoparticles with High MRI Contrast Enhancement for Tumor Imaging". Small First published online: 18 DEC 2013
34. Xin Zhang, Lei Guo, Xiang Li, Tuo Zhang, Dajiang Zhu, Kaiming Li, Hanbo Chen, Jinglei Lv, Changfeng Jin, Qun Zhao, Lingjiang Li, Tianming Liu. " Characterization of Task-free and Task-performance Brain States via Functional Connectome Patterns". Medical Image Analysis Volume 17, Issue 8, December 2013, Pages 1106 -1122.
33. , Wang L, Cheng R, Mao L, Arnold RD, Howerth EW, Chen ZG, Platt S. "Magnetic Nanoparticle-Based Hyperthermia for Head & Neck Cancer in Mouse Models". Theranostics 2012; 2(1):113-121
32. Degang Zhang, Lei Guo, Dajiang Zhu, Kaiming Li, Longchuan Li, Hanbo Chen, Zhao Q., Xiaoping Hu, and Tianming Liu. "Diffusion Tensor Imaging Reveals Evolution of Primate Brain Architectures". Brain Structure and Function Published on line Nov., 2012
31. Jingxin Nie, Lei Guo, Kaiming Li, Yonghua Wang, Guojun Chen, Longchuan Li, Hanbo Chen, Fan Deng, Xi Jiang, Tuo Zhang, Ling Huang, Carlos Faraco, Degang Zhang, Xintao Hu, Gang Li, Jinglei Lv, Yixuan Yuan, Dajiang Zhu, Junwei Han, Dean Sabatinelli, Zhao Q., Haini Cai, L Stephen Miller, Bingqian Xu, Ping Shen, Xiaoping Hu, Tianming Liu. "Axonal Fiber Terminations Concentrate on Gyri."Cerebral Cortex December 2012;22:2831-2839
30. Abell, J., Lee, J., Szu, H., Zhao, Q., Zhao, YP. "Differentiating Intrinsic SERS Spectra from a Mixture by Sampling Induced Composition Gradient and Independent Component Analysis". Analyst Jan. 2012, 137, 73-76, DOI: 10.1039/c1an15623c
29. Langley, J., Potter, W., Huang, F., and "A self-reference PRF-shift MR thermometry method utilizing the phase gradient". Dec. 2011 Phys. Med. Biol. 56 N307
28. Lee, J., Platt,S., Kent, M., and "An analysis of the pharmacokinetic parameter ratios in DCE-MRI using the reference region model".Magnetic Resonance Imaging 2012 Jan;30(1):26-35. doi: 10.1016/j.mri.2011.09.005. Epub 2011 Nov 8.
27. McCully, KK., Mulcahy, TA., Ryan, T., and "Skeletal muscle metabolism in individuals with spinal cord injury" Journal of Applied Physiology 111(1):143-148, 2011
26. , Langley, J., Lee, S., and Liu, W. "Positive contrast technique for detection and quantification of superparamagnetic iron oxide nanoparticles in magnetic resonance imaging". NMR in Biomedicine 24(5): 464-472, 2011
25. Langley, J., Liu, W., Jordon, E. K.., Frank, J. A., and . "Quantification of SPIO nanoparticles in vivo using the finite perturber method".Magnetic Resonance in Medicine 65(5):1461-1469, 2011