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Objective: Accurate estimation of SAR is critical to safeguarding vulnerable patients who require an MRI procedure. The increased static field strength and RF duty cycle capabilities in modern MRI scanners mean that systems can easily exceed safe SAR levels for patients. Advisory protocols routinely used to establish quality assurance protocols are not required to advise on the testing of MRI SAR levels and is not routinely measured in annual medical physics quality assurance checks. This study aims to develop a head phantom and protocol that can independently verify global SAR for MRI clinical scanners. Methods: A four-channel birdcage head coil was used for RF transmission and signal reception. Proton resonance shift thermometry was used to estimate SAR. The SAR estimates were verified by comparing results against two other independent measures, then applied to a further four scanners at field strengths of 1.5 T and 3 T. Results: Scanner output SAR values ranged from 0.42 to 1.52 W/kg. Percentage SAR differences between independently estimated values and those calculated by the scanners differed by 0-2.3%. Conclusion: We have developed a quality assurance protocol to independently verify the SAR output of MRI scanners.
Purpose: To develop bone material analogues that can be used in construction of phantoms for simultaneous PET/MRI systems. Methods: Plaster was used as the basis for the bone material analogues tested in this study. It was mixed with varying concen
Physical head phantoms allow assessing source reconstruction procedures in electroencephalography and electrical stimulation profiles during transcranial electric stimulation. Volume conduction in the head is strongly influenced by the skull represen
In pTx MRI systems, the prediction of local SAR is based on numerical electromagnetic (EM) simulations and used to scale RF power to ensure FDA SAR limits are not exceeded. This prediction becomes more complex when superposition of E-fields from mult
Cross-term spatiotemporal encoding (xSPEN) is a recently introduced imaging approach delivering single-scan 2D NMR images with unprecedented resilience to field inhomogeneities. The method relies on performing a pre-acquisition encoding and a subsequ
Computational models of biophysical tissue properties have been widely used in diffusion MRI (dMRI) research to elucidate the link between microstructural properties and MR signal formation. For brain tissue, the research community has developed the