This is a revised application for 1R01 DA21146-01, which was originally submitted in May, 2005. Magnetic resonance imaging (MRI) and spectroscopy (MRS) are powerful techniques for assessing structure and chemistry or metabolism of the human brain in vivo. These techniques afford relatively high spatial and temporal resolution, are non-invasive and repeatable, and may be performed in children. However, motion continues to be a substantial problem in many MR studies, especially those performed in children, infants, or subjects who are agitated or confused due to anxiety, drug use or sickness, resulting in data with motion artifacts that could prevent accurate diagnoses or assessments. Therefore, the overarching technical goals of this BRP are to develop (1) an optical head tracking system that is highly accurate and robust, with a potential time resolution in the millisecond range, and (2) real-time adaptive MRS and MRS techniques for use with the tracking system. The tracking system will utilize recently-developed """"""""retrograte reflectors"""""""", or RGRs, that allow accurate measurement of full pose with a single marker and a single camera. In parallel, we will develop MRI and MRS pulse sequences that allow motion correction WITHIN single acquisitions, at a time resolution of 10ms. The final adaptive motion correction system and sequences will be validated extensively in three target populations that are prone to motion: 1) children (3-7 years old) who were exposed to methamphetamine in utero, 2) hospitalized in- patients who require repeat MRI scans due to excessive motion, and 3) patients with head tremors. We have assembled a team of experienced investigators who are experts in their respective areas. The PI of the project is Thomas Ernst (University of Hawaii), an MR physicist who will coordinate the overall project and develop techniques for real-time motion correction in MRI and MRS. Other lead investigators are: Brian S.R. Armstrong, Ph.D., (University of Wisconsin in Milwaukee) will develop a real-time, RGR-based motion tracking system. Thomas Prieto, Ph.D. (Medical College of Wisconsin) will be responsible for the overall engineering of the tracking and calibration system specifically within the confines of an MRI scanner. Oliver Speck, Ph.D. (University of Freiburg, Germany), will be responsible for developing MRI sequences with within-scan motion correction. Dr. Speck's group also developed a unique software package that allows real-time control of MRI scans from external devices Dr. Gerhard Laub from Siemens Medical Solutions agreed to be a Technical Advisor to the project. Finally, human subject activities, especially the final validation of the system, will be guided by a Medical Advisory Board with four physician members.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Research Project (R01)
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Special Emphasis Panel (ZRG1-SBIB-J (50))
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Rapaka, Rao
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University of Hawaii
Schools of Medicine
United States
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Yarach, Uten; Tung, Yi-Hang; Setsompop, Kawin et al. (2018) Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging. Magn Reson Med 80:1577-1587
Mattern, Hendrik; Sciarra, Alessandro; Godenschweger, Frank et al. (2018) Prospective motion correction enables highest resolution time-of-flight angiography at 7T. Magn Reson Med 80:248-258
Milovic, Carlos; Acosta-Cabronero, Julio; Pinto, José Miguel et al. (2018) A new discrete dipole kernel for quantitative susceptibility mapping. Magn Reson Imaging 51:7-13
Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik et al. (2017) T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 ?m. Sci Data 4:170032
Yarach, Uten; In, Myung-Ho; Chatnuntawech, Itthi et al. (2017) Model-based iterative reconstruction for single-shot EPI at 7T. Magn Reson Med 78:2250-2264
Zaitsev, Maxim; Akin, Burak; LeVan, Pierre et al. (2017) Prospective motion correction in functional MRI. Neuroimage 154:33-42
Yakupov, Renat; Lei, Juan; Hoffmann, Michael B et al. (2017) False fMRI activation after motion correction. Hum Brain Mapp 38:4497-4510
Herbst, M; Poser, B A; Singh, A et al. (2017) Motion correction for diffusion weighted SMS imaging. Magn Reson Imaging 38:33-38
Yarach, Uten; Luengviriya, Chaiya; Stucht, Daniel et al. (2016) Correction of B 0-induced geometric distortion variations in prospective motion correction for 7T MRI. MAGMA 29:319-32
Godenschweger, F; Kägebein, U; Stucht, D et al. (2016) Motion correction in MRI of the brain. Phys Med Biol 61:R32-56

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