Magnetic resonance imaging has demonstrated the potential for non-invasive mapping of the structural and functional connectivity of the human brain in health and disease. The primary methods that have emerged include diffusion imaging and resting-state functional connectivity mapping. Although these methods have validated capabilities for connectivity mapping, they also face technical limitations which constrain their utility. Diffusion imaging is hampered by low sensitivity and the inefficiency of encoding the diffusion data. Similarly, resting-state functional connectivity is limited in temporal resolution by spatial encoding during whole brain connectivity mapping. In this research project, we hypothesize that we can greatly improve the efficiency of the data acquisition schemes in these methods via multi-slice encoding and simultaneous refocusing acquisition. For example, by increasing the number of images slices obtained per acquisition period from 1 slice to up to 6, we both increase the sensitivity of the data acquisition and greatly reduce the imaging time. This development will help advance an entire class of emerging diffusion methodology which probe the water diffusion and thus white matter and grey matter connectivity in increasing detail over the traditional diffusion tensor image. Similarly, it will increase the spatial-temporal resolution and the sensitivity of resting-state functional connectivity mapping. Improving sensitivity and reduce acquisition time will pave way for routine clinical and clinical science applications of these technologies. During the mentored phase of the project, the candidate will draw on his signal processing and optimization theory expertise to design RF pulses and reconstruction algorithms, while gaining knowledge in neuroscience and MR physic to develop acquisition sequences, as well as process and interpret the brain connectivity data. In the later stage, by combining various components of this project, experiments will be carried out to obtain high signal in vivo data in clinically relevant time frame for resting-state functional connectivity mapping and diffusion imaging via DTI, Q-ball, and DSI. The project fits the candidate's long-term career goal of establishing a high-quality independent research program on data acquisition methodology in MRI that will fully utilizes the knowledge and the inter-play between software algorithm development, MR physic, and the underlying neuroscience. The mentored phase will be carried out at the MGH Martinos Center for Biomedical Imaging where the candidate will take advantage of the advanced high-field MRI facility and expertise. Furthermore, the candidate will make use of the world renowned educational opportunities at the Center's affiliated institutions (MIT and Harvard). His career development plan includes training in MR physics and sequence design, diffusion imaging and brain connectomics, consultations with experts and coursework in neuroscience;and participation in seminars and scientific meetings. As part of initiating his own independent research program, the candidate will help mentor a graduate student who will be involved in this project.
Diffusion imaging and resting-state fMRI are potent methods for visualizing pathology and mapping connectivity in the brain. This work will develop highly efficient data acquisition scheme to increase speed and sensitivity of these methods, thus making them more applicable for clinical use.
|McDaniel, Patrick; Bilgic, Berkin; Fan, Audrey P et al. (2017) Mitigation of partial volume effects in susceptibility-based oxygenation measurements by joint utilization of magnitude and phase (JUMP). Magn Reson Med 77:1713-1727|
|Raij, Tommi; Nummenmaa, Aapo; Marin, Marie-France et al. (2017) Prefrontal Cortex Stimulation Enhances Fear Extinction Memory in Humans. Biol Psychiatry :|
|Setsompop, Kawin; Feinberg, David A; Polimeni, Jonathan R (2016) Rapid brain MRI acquisition techniques at ultra-high fields. NMR Biomed 29:1198-221|
|Ye, Huihui; Ma, Dan; Jiang, Yun et al. (2016) Accelerating magnetic resonance fingerprinting (MRF) using t-blipped simultaneous multislice (SMS) acquisition. Magn Reson Med 75:2078-85|
|Bilgic, Berkin; Xie, Luke; Dibb, Russell et al. (2016) Rapid multi-orientation quantitative susceptibility mapping. Neuroimage 125:1131-1141|
|Bo Zhao; Haldar, Justin P; Setsompop, Kawin et al. (2016) Optimal experiment design for magnetic resonance fingerprinting. Conf Proc IEEE Eng Med Biol Soc 2016:453-456|
|Zhao, Bo; Setsompop, Kawin; Ye, Huihui et al. (2016) Maximum Likelihood Reconstruction for Magnetic Resonance Fingerprinting. IEEE Trans Med Imaging 35:1812-23|
|Ning, Lipeng; Setsompop, Kawin; Michailovich, Oleg et al. (2016) A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging. Neuroimage 125:386-400|
|Ning, Lipeng; Setsompop, Kawin; Michailovich, Oleg et al. (2015) A Compressed-Sensing Approach for Super-Resolution Reconstruction of Diffusion MRI. Inf Process Med Imaging 24:57-68|
|Bilgic, Berkin; Gagoski, Borjan A; Cauley, Stephen F et al. (2015) Wave-CAIPI for highly accelerated 3D imaging. Magn Reson Med 73:2152-62|
Showing the most recent 10 out of 25 publications