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Novel spin-lock time sampling strategies for improved reproducibility in quantitative T1ρ mapping
Sandeep Panwar Jogi1, Qi Peng2, Ramin Jafari3
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
NMR in Biomedicine
|August 17, 2024
Summary
New sampling schemes for spin-lock times in quantitative T1ρ mapping significantly improve reproducibility. These methods, reproducibility-guided random sampling (RRS) and reproducibility-guided optimal sampling (ROS), are crucial for accurate disease monitoring.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Quantitative Imaging
- Biomedical Engineering
Background:
- Quantitative T1ρ mapping is essential for assessing tissue properties.
- Reproducibility in T1ρ measurements is critical for reliable clinical applications.
- Existing spin-lock time (TSL) sampling schemes may limit measurement accuracy.
Purpose of the Study:
- To develop and evaluate novel TSL sampling schemes for enhanced reproducibility in quantitative T1ρ mapping.
- To compare the performance of new schemes against existing methods under various conditions.
Main Methods:
- Proposed reproducibility-guided random sampling (RRS) and reproducibility-guided optimal sampling (ROS) schemes.
- Evaluated schemes using numerical simulations, phantom experiments, and volunteer studies.
- Assessed reproducibility via coefficient of variation (CoV) and investigated effects of field inhomogeneities.
Main Results:
- RRS and ROS demonstrated significantly lower mean CoVs compared to linear sampling (LS) and precision-guided sampling (PS) in simulations and phantom studies.
- Proposed schemes showed improved reproducibility under B1 field inhomogeneity (20% offset) and B0 field inhomogeneity (>50 Hz).
- Volunteer studies confirmed lower CoVs for RRS and ROS in thigh muscles.
Conclusions:
- The proposed RRS and ROS sampling schemes enhance the reproducibility of quantitative T1ρ mapping.
- Optimized TSL selection leads to more reliable measurements, beneficial for longitudinal studies tracking disease progression and treatment response.
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