# Acquisition and Analysis Methods for Hyperpolarized MR Data

> **NIH NIH P41** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $375,580

## Abstract

TRD3 PROJECT SUMMARY/ABSTRACT
Specialized fast acquisitions are a necessity for HP MRI studies by the CPs and SPs, dictating that data
reconstruction and analysis software platforms must be flexible and expansive, covering a variety of coil
geometries, k-space trajectories, vascular delivery and molecular kinetics. The analysis of HP MRI data also
requires specialized methods that account for the bolus kinetics and vascular effects as well as specialized
evaluation approaches since ground truth data is typically not available for comparison. The challenges
remaining for HP acquisition and analysis include quantifying kinetics, heterogeneity of strategies across the
user community, and how to leverage data-driven, machine learning methods for HP MRI. To provide next
generation HP technology as well as to enable multi-site data harmonization and large-scale data analysis, the
Main goals of TRD3: Acquisition and Analysis Methods for Hyperpolarized MR Data are to:
 1) Develop next-generation pulse sequences, reconstruction methods, and analysis methods for HP-13C
 MRI to provide improved spatio-temporal resolution, coverage, and sensitivity to metabolism;
 2) Create standardized methods (phantoms and protocols) to enable multi-site comparison and trials;
 3) Provide advanced HP tools through open-source software that will support next generation acquisition
 and analysis innovations throughout the CPs, SPs and the HP MRI community;
 4) Develop HP MRI analyses that are integrated with other imaging and clinical data.
These will be achieved through the following aims, driven by push-pull collaborations with the CPs:
Aim 1) Development of novel high-resolution and robust acquisitions to improve the utilization of HP signals to
achieve consistent data acquisition, enabling interrogation of metabolic processes
Aim 2) Development of specialized analysis methods to enable robust and reliable interpretation of HP data
Aim 3) Improved management and infrastructure for visualization, integration and sharing of data
The resulting techniques will be disseminated through free, open-source software to service projects and the
general scientific community using our established software frameworks (SIVIC, hyperpolarized-mri-toolbox)
and through the new website, hyperpolarizedmri.ucsf.edu.

## Key facts

- **NIH application ID:** 10410337
- **Project number:** 2P41EB013598-11
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** DUAN XU
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $375,580
- **Award type:** 2
- **Project period:** 2011-08-01 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10410337

## Citation

> US National Institutes of Health, RePORTER application 10410337, Acquisition and Analysis Methods for Hyperpolarized MR Data (2P41EB013598-11). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10410337. Licensed CC0.

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