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 1 aims to replace traditional complex and inefficient imaging protocols with simple, comprehensive acquisitions that also yield quantitative parameters sensitive to specific disease processes. In the first funding period of this P41 Center, our project team led the way in establishing rapid, continuous, comprehensive imaging methods, which are now available on a growing number of commercial magnetic resonance imaging (MRI) scanners worldwide. This foundation will allow us, in the proposed research plan for the next period, to enrich our data streams, to advance the extraction of actionable information from those data streams, and to feed the resulting information back into the design of our acquisition software and hardware. Thanks to developments during our first funding period, we are now in a position to question long-established assumptions about scanner design, originating from the classical imaging pipeline of human radiologists interpreting multiple series of qualitative images. We will reimagine the process of MR scanning, leveraging our core expertise in pulse-sequence design, parallel imaging, compressed sensing, model-based image reconstruction and machine learning. We will also extend our methods to complex multifaceted data streams, arising not only from MRI but also from Positron Emission Tomography (PET) and other imaging modalities, as well as from diverse arrays of complementary sensors.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Biotechnology Resource Grants (P41)
Project #
5P41EB017183-07
Application #
9996679
Study Section
Special Emphasis Panel (ZEB1)
Project Start
2014-09-30
Project End
2024-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
7
Fiscal Year
2020
Total Cost
Indirect Cost
Name
New York University
Department
Type
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
Benkert, Thomas; Mugler 3rd, John P; Rigie, David S et al. (2018) Hybrid T2 - and T1 -weighted radial acquisition for free-breathing abdominal examination. Magn Reson Med 80:1935-1948
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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

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