Nan-kuei Chen

Nan-kuei Chen

Associate Professor, Biomedical Engineering
Associate Professor, BIO5 Institute
Primary Department
Department Affiliations
Contact
(520) 626-0060

Research Interest

Research Interest

I am an MR physicist with extensive expertise in fast image acquisition methodology, pulse sequence design, and artifact correction for neuro MRI. In the past 18 years, I have developed novel approaches effectively addressing various types of challenging MRI artifacts, ranging from echo-planar imaging (EPI) geometric distortions, to susceptibility effect induced signal loss, to EPI Nyquist artifact, to motion-induced phase errors and aliasing artifacts in interleaved EPI based diffusion-weighted imaging. I am the original developer of multiplexed sensitivity encoded (MUSE) MRI, which can measure human brain connectivity in vivo at high spatial-resolution and accuracy, as shown in the publications listed below. More generally, my research involves the application of MR protocols in translational contexts. I have served as PI on NIH-funded R01, R21 and R03 grants, and have had extensive experience as a co-investigator on NIH-funded projects. The current focus of my research includes: * Development of high-throughput and motion-immune clinical MRI for imaging challenging patient populations * Imaging of neuronal connectivity networks for studies of neurological diseases * High-fidelity and multi-contrast MRI guided intervention * Characterization and correction of MRI artifacts * Signal processing and algorithm development * MRI studies of human development

Publications

Milles, J., Zhu, Y. M., Chen, N., Panych, L. P., Gimenez, G., & Guttmann, C. R. (2006). Computation of transmitted and received B1 fields in magnetic resonance imaging. IEEE transactions on bio-medical engineering, 53(5), 885-95.

Computation of B1 fields is a key issue for determination and correction of intensity nonuniformity in magnetic resonance images. This paper presents a new method for computing transmitted and received B1 fields. Our method combines a modified MRI acquisition protocol and an estimation technique based on the Levenberg-Marquardt algorithm and spatial filtering. It enables accurate estimation of transmitted and received B1 fields for both homogeneous and heterogeneous objects. The method is validated using numerical simulations and experimental data from phantom and human scans. The experimental results are in agreement with theoretical expectations.

Truong, T., Chen, N., & Song, A. W. (2012). Inherent correction of motion-induced phase errors in multishot spiral diffusion-weighted imaging. Magnetic resonance in medicine, 68(4), 1255-61.

Multishot spiral imaging is a promising alternative to echo-planar imaging for high-resolution diffusion-weighted imaging and diffusion tensor imaging. However, subject motion in the presence of diffusion-weighting gradients causes phase inconsistencies among different shots, resulting in signal loss and aliasing artifacts in the reconstructed images. Such artifacts can be reduced using a variable-density spiral trajectory or a navigator echo, however at the cost of a longer scan time. Here, a novel iterative phase correction method is proposed to inherently correct for the motion-induced phase errors without requiring any additional scan time. In this initial study, numerical simulations and in vivo experiments are performed to demonstrate that the proposed method can effectively and efficiently correct for spatially linear phase errors caused by rigid-body motion in multishot spiral diffusion-weighted imaging of the human brain.

Guhaniyogi, S., Chu, M., Chang, H., Song, A. W., & Chen, N. (2016). Motion immune diffusion imaging using augmented MUSE for high-resolution multi-shot EPI. Magnetic resonance in medicine, 75(2), 639-52.

To develop new techniques for reducing the effects of microscopic and macroscopic patient motion in diffusion imaging acquired with high-resolution multishot echo-planar imaging.

Yoo, S., Fairneny, T., Chen, N., Choo, S., Panych, L. P., Park, H., Lee, S., & Jolesz, F. A. (2004). Brain-computer interface using fMRI: spatial navigation by thoughts. Neuroreport, 15(10), 1591-5.

A brain-computer interface (BCI) is a way of conveying an individual's thoughts to control computer or electromechanical hardware. Capitalizing on the ability to characterize brain activity in a reproducible manner, we explored the possibility of using real-time fMRI to interpret the spatial distribution of brain function as BCI commands. Using a high-field (3T) MRI scanner, brain activities associated with four distinct covert functional tasks were detected and subsequently translated into predetermined computer commands for moving four directional cursors. The proposed fMRI-BCI method allowed volunteer subjects to navigate through a simple 2D maze solely through their thought processes.

Sundman, M. H., Chen, N. K., Subbian, V., & Chou, Y. H. (2017). The bidirectional gut-brain-microbiota axis as a potential nexus between traumatic brain injury, inflammation, and disease. Brain, behavior, and immunity, 66, 31-44.

As head injuries and their sequelae have become an increasingly salient matter of public health, experts in the field have made great progress elucidating the biological processes occurring within the brain at the moment of injury and throughout the recovery thereafter. Given the extraordinary rate at which our collective knowledge of neurotrauma has grown, new insights may be revealed by examining the existing literature across disciplines with a new perspective. This article will aim to expand the scope of this rapidly evolving field of research beyond the confines of the central nervous system (CNS). Specifically, we will examine the extent to which the bidirectional influence of the gut-brain axis modulates the complex biological processes occurring at the time of traumatic brain injury (TBI) and over the days, months, and years that follow. In addition to local enteric signals originating in the gut, it is well accepted that gastrointestinal (GI) physiology is highly regulated by innervation from the CNS. Conversely, emerging data suggests that the function and health of the CNS is modulated by the interaction between 1) neurotransmitters, immune signaling, hormones, and neuropeptides produced in the gut, 2) the composition of the gut microbiota, and 3) integrity of the intestinal wall serving as a barrier to the external environment. Specific to TBI, existing pre-clinical data indicates that head injuries can cause structural and functional damage to the GI tract, but research directly investigating the neuronal consequences of this intestinal damage is lacking. Despite this void, the proposed mechanisms emanating from a damaged gut are closely implicated in the inflammatory processes known to promote neuropathology in the brain following TBI, which suggests the gut-brain axis may be a therapeutic target to reduce the risk of Chronic Traumatic Encephalopathy and other neurodegenerative diseases following TBI. To better appreciate how various peripheral influences are implicated in the health of the CNS following TBI, this paper will also review the secondary biological injury mechanisms and the dynamic pathophysiological response to neurotrauma. Together, this review article will attempt to connect the dots to reveal novel insights into the bidirectional influence of the gut-brain axis and propose a conceptual model relevant to the recovery from TBI and subsequent risk for future neurological conditions.