The temperature dependence of gradient system response characteristics.

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Medical Physics
• Engineering

Background:

• The gradient system transfer function (GSTF) is crucial for characterizing dynamic gradient system behavior.
• Accurate GSTF is essential for correcting non-Cartesian k-space trajectories in MRI.
• Understanding temperature effects on GSTF is vital for maintaining image quality and scanner performance.

Purpose of the Study:

• To analyze the impact of gradient coil temperature on the GSTF of a 3T MRI scanner.
• To investigate the temperature dependency of GSTF self- and B0-cross-terms.
• To evaluate different modeling approaches for temperature-induced GSTF variations.

Main Methods:

• Acquired GSTF self- and B0-cross-terms using a phantom-based measurement technique on a 3T Siemens scanner.
• Measured GSTF terms across various temperature states up to 45°C.
• Utilized 12 integrated temperature sensors for continuous gradient coil temperature monitoring and compared different modeling strategies.

Main Results:

• GSTF self-terms exhibit a linear dependence on temperature, while B0-cross-terms do not show significant thermal variation.
• Thermal variations have negligible effects on the phase response.
• A linear model incorporating three key gradient coil sensors best represented self-terms; a convolution model was suitable for B0-cross-terms.

Conclusions:

• Temperature dependency of GSTF was successfully analyzed for a 3T Siemens scanner.
• Both self- and B0-cross-terms of GSTF can be effectively modeled using linear and convolution approaches, respectively.
• The proposed modeling relies on three main temperature sensor elements for accurate characterization.