TY  - JOUR
A1  - Stich, Manuel
A1  - Pfaff, Christiane
A1  - Wech, Tobias
A1  - Slawig, Anne
A1  - Ruyters, Gudrun
A1  - Dewdney, Andrew
A1  - Ringler, Ralf
A1  - Köstler, Herbert
T1  - The temperature dependence of gradient system response
characteristics
JF  - Magnetic Resonance in Medicine
N2  - Purpose:
The gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non‐Cartesian k‐space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF.

Methods:
GSTF self‐ and B\(_0\)‐cross‐terms were acquired for a 3T Siemens scanner (Siemens Healthcare, Erlangen, Germany) using a phantom‐based measurement technique. The GSTF terms were measured for various temperature states up to 45°C. The gradient coil temperatures were measured continuously utilizing 12 temperature sensors which are integrated by the vendor. Different modeling approaches were applied and compared. 

Results:
The self‐terms depend linearly on temperature, whereas the B0‐cross‐term does not. Effects induced by thermal variation are negligible for the phase response. The self‐terms are best represented by a linear model including the three gradient coil sensors that showed the maximum temperature dependence for the three axes. The use of time derivatives of the temperature did not lead to an improvement of the model. The B\(_0\)‐cross‐terms can be modeled by a convolution model which considers coil‐specific heat transportation. 

Conclusion:
The temperature dependency of the GSTF was analyzed for a 3T Siemens scanner. The self‐ and B0‐cross‐terms can be modeled using a linear and convolution modeling approach based on the three main temperature sensor elements.
KW  - gradient impulse response function
KW  - gradient system respose
KW  - gradient system trasfer function
KW  - temperature dependency
KW  - thermal variation
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-206212
VL  - 83
ER  - 
TY  - JOUR
A1  - Richter, Julian A. J.
A1  - Wech, Tobias
A1  - Weng, Andreas M.
A1  - Stich, Manuel
A1  - Weick, Stefan
A1  - Breuer, Kathrin
A1  - Bley, Thorsten A.
A1  - Köstler, Herbert
T1  - Free‐breathing self‐gated 4D lung MRI using wave‐CAIPI
JF  - Magnetic Resonance in Medicine
N2  - Purpose
The aim of this study was to compare the wave‐CAIPI (controlled aliasing in parallel imaging) trajectory to the Cartesian sampling for accelerated free‐breathing 4D lung MRI.

Methods
The wave‐CAIPI k‐space trajectory was implemented in a respiratory self‐gated 3D spoiled gradient echo pulse sequence. Trajectory correction applying the gradient system transfer function was used, and images were reconstructed using an iterative conjugate gradient SENSE (CG SENSE) algorithm. Five healthy volunteers and one patient with squamous cell carcinoma in the lung were examined on a clinical 3T scanner, using both sampling schemes. For quantitative comparison of wave‐CAIPI and standard Cartesian imaging, the normalized mutual information and the RMS error between retrospectively accelerated acquisitions and their respective references were calculated. The SNR ratios were investigated in a phantom study.

Results
The obtained normalized mutual information values indicate a lower information loss due to acceleration for the wave‐CAIPI approach. Average normalized mutual information values of the wave‐CAIPI acquisitions were 10% higher, compared with Cartesian sampling. Furthermore, the RMS error of the wave‐CAIPI technique was lower by 19% and the SNR was higher by 14%. Especially for short acquisition times (down to 1 minute), the undersampled Cartesian images showed an increased artifact level, compared with wave‐CAIPI.

Conclusion
The application of the wave‐CAIPI technique to 4D lung MRI reduces undersampling artifacts, in comparison to a Cartesian acquisition of the same scan time. The benefit of wave‐CAIPI sampling can therefore be traded for shorter examinations, or enhancing image quality of undersampled 4D lung acquisitions, keeping the scan time constant.
KW  - free‐breathing
KW  - lung
KW  - self‐gated
KW  - wave‐CAIPI
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-218075
VL  - 84
IS  - 6
SP  - 3223
EP  - 3233
ER  -