This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.We are continuing our efforts to redefine and improve upon the methodology of DWI and diffusion tensor imaging (DTI) for the investigators and collaborators on the P41 RR09784 Center for Advanced MR Technology at Stanford effort. SENSitivity Encoding (SENSE) is a valuable complement to regular gradient encoding in MRI. It employs some of the spatial information contained in the individual elements in an RF coil array to achieve a considerable reduction of scanning time. For this reason, SENSE is a promising concept in view of physiological as well as technical limits to efficiently traverse k-space. SENSE can be used to accelerate virtually any conventional MRI technique without interfering with typical contrast mechanisms used in MRI, such as diffusion-weighted imaging (DWI). Despite well-known problems, in most cases EPI is still the method of choice for acquiring in-vivo DWI data. With recent achievements in scanning diffusion properties more uniformly in space and resolving more details in voxels that contain more than one fiber tract, the number of measurements has tremendously increased and the role of EPI as a vehicle for fast data acquisition has become even more important.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR009784-13
Application #
7601899
Study Section
Special Emphasis Panel (ZRG1-SBIB-F (40))
Project Start
2007-06-01
Project End
2008-05-31
Budget Start
2007-06-01
Budget End
2008-05-31
Support Year
13
Fiscal Year
2007
Total Cost
$23,028
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Maclaren, Julian; Aksoy, Murat; Ooi, Melvyn B et al. (2018) Prospective motion correction using coil-mounted cameras: Cross-calibration considerations. Magn Reson Med 79:1911-1921
Guo, Jia; Holdsworth, Samantha J; Fan, Audrey P et al. (2018) Comparing accuracy and reproducibility of sequential and Hadamard-encoded multidelay pseudocontinuous arterial spin labeling for measuring cerebral blood flow and arterial transit time in healthy subjects: A simulation and in vivo study. J Magn Reson Imaging 47:1119-1132
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Lai, Lillian M; Cheng, Joseph Y; Alley, Marcus T et al. (2017) Feasibility of ferumoxytol-enhanced neonatal and young infant cardiac MRI without general anesthesia. J Magn Reson Imaging 45:1407-1418
Taviani, Valentina; Alley, Marcus T; Banerjee, Suchandrima et al. (2017) High-resolution diffusion-weighted imaging of the breast with multiband 2D radiofrequency pulses and a generalized parallel imaging reconstruction. Magn Reson Med 77:209-220
Uecker, Martin; Lustig, Michael (2017) Estimating absolute-phase maps using ESPIRiT and virtual conjugate coils. Magn Reson Med 77:1201-1207
Kogan, Feliks; Hargreaves, Brian A; Gold, Garry E (2017) Volumetric multislice gagCEST imaging of articular cartilage: Optimization and comparison with T1rho. Magn Reson Med 77:1134-1141
Aksoy, Murat; Maclaren, Julian; Bammer, Roland (2017) Prospective motion correction for 3D pseudo-continuous arterial spin labeling using an external optical tracking system. Magn Reson Imaging 39:44-52
Suh, Ga-Young; Choi, Gilwoo; Herfkens, Robert J et al. (2016) Three-Dimensional Modeling Analysis of Visceral Arteries and Kidneys during Respiration. Ann Vasc Surg 34:250-60
Ong, Frank; Lustig, Michael (2016) Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition. IEEE J Sel Top Signal Process 10:672-687

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