Abstract

Technology Research and Development Project #3 Advancing MR and PET Through Synergistic Simultaneous Acquisition and Joint Reconstruction TR&D #3 Principal Investigators: Fernando Boada, PhD, Yu-Shin Ding, PhD, and Johan Nuyts, PhD The broad mission of our Center for Advanced Imaging Innovation and Research (CAI2R) is to bring together collaborative translational research teams for the development of high-impact biomedical imaging technologies, with the ultimate goal of changing day-to-day clinical practice. Technology Research and Development (TR&D) project #3 is addressed at new uses of simultaneity, advancing the fundamental capabilities of MR and PET through synergistic simultaneous acquisition and joint reconstruction.
Specific aims are as follows: (1) Develop MR-based motion correction algorithms for PET. (2) Develop constrained reconstruction approaches for PET and combined MR-PET. (3) Develop and validate integrated physiological modeling for concurrently acquired MR and PET data. (4) Develop MR-PET tracers to support collaborative and service projects.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Biotechnology Resource Grants (P41)
Project #
1P41EB017183-01A1
Application #
8794075
Study Section
Special Emphasis Panel (ZEB1-OSR-E (O1))
Project Start
Project End
Budget Start
2014-09-30
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
$486,632
Indirect Cost
$123,476

  Institution

Name
New York University
Department
Type
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016

  Publications

Feng, Li; Coppo, Simone; Piccini, Davide et al. (2018) 5D whole-heart sparse MRI. Magn Reson Med 79:826-838
Benkert, Thomas; Tian, Ye; Huang, Chenchan et al. (2018) Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding. Magn Reson Med 80:286-293
Wake, Nicole; Chandarana, Hersh; Rusinek, Henry et al. (2018) Accuracy and precision of quantitative DCE-MRI parameters: How should one estimate contrast concentration? Magn Reson Imaging 52:16-23
Lee, Hong-Hsi; Sodickson, Daniel K; Lattanzi, Riccardo (2018) An analytic expression for the ultimate intrinsic SNR in a uniform sphere. Magn Reson Med 80:2256-2266
Lattanzi, Riccardo; Zhang, Bei; Knoll, Florian et al. (2018) Phase unwinding for dictionary compression with multiple channel transmission in magnetic resonance fingerprinting. Magn Reson Imaging 49:32-38
Madelin, Guillaume; Xia, Ding; Brown, Ryan et al. (2018) Longitudinal study of sodium MRI of articular cartilage in patients with knee osteoarthritis: initial experience with 16-month follow-up. Eur Radiol 28:133-142
Sbrizzi, Alessandro; Heide, Oscar van der; Cloos, Martijn et al. (2018) Fast quantitative MRI as a nonlinear tomography problem. Magn Reson Imaging 46:56-63
Lakshmanan, Karthik; Brown, Ryan; Madelin, Guillaume et al. (2018) An eight-channel sodium/proton coil for brain MRI at 3 T. NMR Biomed 31:
Winters, Kerryanne V; Reynaud, Olivier; Novikov, Dmitry S et al. (2018) Quantifying myofiber integrity using diffusion MRI and random permeable barrier modeling in skeletal muscle growth and Duchenne muscular dystrophy model in mice. Magn Reson Med 80:2094-2108
Hammernik, Kerstin; Klatzer, Teresa; Kobler, Erich et al. (2018) Learning a variational network for reconstruction of accelerated MRI data. Magn Reson Med 79:3055-3071

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