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MTTA: Multi-tensor based tract analysis for diffusion MRI in clinical research

发布日期:2012-05-05 16:11:43      浏览次数:

MTTA: Multi-tensor based tract analysis for diffusion MRI in clinical research
Time: 10:00am-12:00pm, June12 (Tuesday)
Location: Room #104, Center for Biomedical Imaging Research, Tsinghua University
Speaker: Hao Huang (Ph.D.Assistant Professor of AIRC and Radiology, University of Texas Southwestern Medical Center, Adjunct Assistant Professor of Radiology, Johns Hopkins University School of Medicine)
 
Abstract
The diffusion MRI in clinical research indicates the diffusion imaging of b value at 1000-1500s/mm2 and 25 to 60 diffusion orientations with imaging time less than 10 minutes. While it is well known that more than one-third of brain voxels of the human brain contain crossing fibers which make current FA values of single tensor significantly underestimated and cause biased results in clinical applications, few studies have been conducted to develop an improved measure which is less affected by widespread crossing fibers in the human brain. Due to extensive applications of the FA in neurological and psychiatric studies such as phenotype characterization, drug testing and therapy monitoring, biased conclusions from the underestimated FA could have a significant negative impact on these studies. Hence it is critical to develop methods which can correct the underestimated FA in these clinical studies. Previous investigations of crossing fibers have been mainly related to correctly revealing the fiber orientations in the voxels of crossing fibers for improvement of tractography. In addition, most of these studies were performed at the cost of high b, high angular resolution and long scanning time which are not suitable for clinical studies. In this project, we propose a novel Multi-Tensor-based Tract Analysis (MTTA) for an improved anisotropy measure which corrects the underestimation of FA of single tensor model at crossing-fiber regions, provides quantified structural information at the tract level, and can be used for data from diffusion MRI in clinical research. With input of diffusion weighted images, MTTA identifies crossing fiber regions first, fully characterizes multiple tensors (a step further than just primary eigenvectors for tractography) at the voxels of crossing fibers and detaches the crossed fibers with a tract analysis. The developed method will increase sensitivity and accuracy in detecting abnormality of white matter.
 
Biography
Dr Huang obtained his bachelor degree from Tsinghua University, China, in 1996. After getting his master degree at Peking University in 1998, he pursued his PhD at Biomedical Engineering graduate program at Johns Hopkins where he has been working on diffusion MRI. In 2005, Dr. Huang obtained his PhD at Johns Hopkins School of Medicine. Immediately after his PhD, he has become a research associate faculty, expanding his skills of diffusion MRI technology and extending his knowledge of brain anatomy, still at Johns Hopkins School of Medicine. He became a tenure-track assistant professor at University of Texas Southwestern Medical Center and set up the Lab of Structural MR Imaging and Analysis two years later in 2007. At the same time, Dr. Huang is an adjunct assistant professor of Johns Hopkins School of Medicine. Dr. Huang is the PI of multiple NIH grants, including R01 and R21. Dr. Huang is also a grant reviewer of NIH, Israel Science Foundation and other international organization and government agency. In addition, Dr. Huang routinely reviews for more than twenty high impact journals including American Journal of Psychiatry, Biological Psychiatry and Neuroimage. Dr. Huang has had more than 35 journal publications in high profile journals, including Journal of Neuroscience, Annals of Neurology and Cerebral Cortex and three of his first-author articles have more than 100 citations for each of them.