Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance

• Published in: Magma (New York, N.Y.) Vol. 34; no. 1; pp. 153 - 163
• Main Authors: Orzada, Stephan, Fiedler, Thomas M., Bitz, Andreas K., Ladd, Mark E., Quick, Harald H.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2021
• Subjects: Basic Science - Interventional; bio-effects; Biomedical Engineering and Bioengineering; Computer Appl. in Life Sciences; Health Informatics; Imaging; Medicine; Medicine & Public Health; Radiology; Research Article; safety; Solid State Physics; VOP compression; Local SAR; Vops; SAR; MRI
• ISSN: 0968-5243; 1352-8661
• DOI: 10.1007/s10334-020-00890-0

Objective In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance. Method Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression. Result Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values. Conclusion The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.