title: Improving SAR estimations in MRI using subject-specific models.
abstract: To monitor and strategically control energy deposition in magnetic resonance imaging (MRI), measured as a specific absorption rate (SAR), numerical methods using generic human models have been employed to estimate worst-case values. Radiofrequency (RF) sequences are therefore often designed conservatively with large safety margins, potentially hindering the full potential of high-field systems. To more accurately predict the patient SAR values, we propose the use of image registration techniques, in conjunction with high-resolution image and tissue libraries, to create patient-specific voxel models. To test this, a matching model from the archives was first selected. Its tissue information was then warped to the patient's coordinates by registering the high-resolution library image to the pilot scan of the patient. Results from studying the models' 1 g SAR distribution suggest that the developed patient model can predict regions of elevated SAR within the patient with remarkable accuracy. Additionally, this work also proposes a voxel analytical metric that can assist in the construction of a patient library and the selection of the matching model from the library for a patient. It is hoped that, by developing voxel models with high accuracy in patient-specific anatomy and positioning, the proposed method can accurately predict the safety margins for high-field human applications and, therefore maximize the safe use of RF sequence power in high-field MRI systems.
authors.affiliation: School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia.
authors.forename: Jin
authors.initials: J
authors.lastname: Jin
authors.forename: Feng
authors.initials: F
authors.lastname: Liu
authors.forename: Ewald
authors.initials: E
authors.lastname: Weber
authors.forename: Stuart
authors.initials: S
authors.lastname: Crozier
mesh_terms: D000042:Absorption; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008954:Models, Biological; D056888:Patient Positioning; D057285:Precision Medicine; D011829:Radiation Dosage