Beschreibung:
<jats:sec><jats:title>Purpose</jats:title><jats:p>To improve the specific absorption rate (SAR) compression model capability in parallel transmission (pTx) MRI systems.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A <jats:italic>k</jats:italic>‐means clustering method is proposed to group voxels with similar SAR behaviors in the scanned object, providing a controlled upper‐bounded estimation of peak local SARs. This <jats:italic>k</jats:italic>‐means compression model and the conventional virtual observation point (VOP) model were tested in a pTx MRI framework. The pTx pulse design with different SAR controlling schemes was simulated using a numerical human head model and an eight‐channel 7T coil array. Multiple criteria (including RF power, global and peak local SARs, and excitation accuracy) were compared for the performance testing.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The <jats:italic>k</jats:italic>‐means compression model generated a narrower overestimation bound, leading to a more accurate local SAR estimation. Among different pTx pulse design approaches, the <jats:italic>k</jats:italic>‐means compression model showed the best trade‐off between the SAR and excitation accuracy.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The developed SAR compression model is advantageous for pTx framework given the narrower overestimation bound and control over the compression ratio. Results also illustrate that a moderate increase of maximum RF power can be useful for reducing the maximum local SAR deposition.</jats:p></jats:sec>