TY - JOUR
T1 - Conditional safety margins for less conservative peak local SAR assessment
T2 - A probabilistic approach
AU - Meliadò, Ettore Flavio
AU - Sbrizzi, Alessandro
AU - van den Berg, Cornelis A T
AU - Steensma, Bart R
AU - Luijten, Peter R
AU - Raaijmakers, Alexander J E
N1 - © 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
Publisher Copyright:
© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine
PY - 2020/12/1
Y1 - 2020/12/1
N2 - PURPOSE: The introduction of a linear safety factor to address peak local specific absorption rate (pSAR10g ) uncertainties (eg, intersubject variation, modeling inaccuracies) bears one considerable drawback: It often results in over-conservative scanning constraints. We present a more efficient approach to define a variable safety margin based on the conditional probability density function of the effectively obtained pSAR10g value, given the estimated pSAR10g value.METHODS: The conditional probability density function can be estimated from previously simulated data. A representative set of true and estimated pSAR10g samples was generated by means of our database of 23 subject-specific models with an 8-fractionated dipole array for prostate imaging at 7 T. The conditional probability density function was calculated for each possible estimated pSAR10g value and used to determine the corresponding safety margin with an arbitrary low probability of underestimation. This approach was applied to five state-of-the-art local SAR estimation methods, namely: (1) using just the generic body model "Duke"; (2) using our model library to assess the maximum pSAR10g value over all models; (3) using the most representative "local SAR model"; (4) using the five most representative local SAR models; and (5) using a recently developed deep learning-based method.RESULTS: Compared with the more conventional safety factor, the conditional safety-margin approach results in lower (up to 30%) mean overestimation for all investigated local SAR estimation methods.CONCLUSION: The proposed probabilistic approach for pSAR10g correction allows more accurate local SAR assessment with much lower overestimation, while a predefined level of underestimation is accepted (eg, 0.1%).
AB - PURPOSE: The introduction of a linear safety factor to address peak local specific absorption rate (pSAR10g ) uncertainties (eg, intersubject variation, modeling inaccuracies) bears one considerable drawback: It often results in over-conservative scanning constraints. We present a more efficient approach to define a variable safety margin based on the conditional probability density function of the effectively obtained pSAR10g value, given the estimated pSAR10g value.METHODS: The conditional probability density function can be estimated from previously simulated data. A representative set of true and estimated pSAR10g samples was generated by means of our database of 23 subject-specific models with an 8-fractionated dipole array for prostate imaging at 7 T. The conditional probability density function was calculated for each possible estimated pSAR10g value and used to determine the corresponding safety margin with an arbitrary low probability of underestimation. This approach was applied to five state-of-the-art local SAR estimation methods, namely: (1) using just the generic body model "Duke"; (2) using our model library to assess the maximum pSAR10g value over all models; (3) using the most representative "local SAR model"; (4) using the five most representative local SAR models; and (5) using a recently developed deep learning-based method.RESULTS: Compared with the more conventional safety factor, the conditional safety-margin approach results in lower (up to 30%) mean overestimation for all investigated local SAR estimation methods.CONCLUSION: The proposed probabilistic approach for pSAR10g correction allows more accurate local SAR assessment with much lower overestimation, while a predefined level of underestimation is accepted (eg, 0.1%).
KW - SAR model library
KW - SAR model selection
KW - parallel transmit
KW - safety factor
KW - specific absorption rate
KW - subject-specific local SAR assessment
UR - http://www.scopus.com/inward/record.url?scp=85085884400&partnerID=8YFLogxK
U2 - 10.1002/mrm.28335
DO - 10.1002/mrm.28335
M3 - Article
C2 - 32492249
SN - 0740-3194
VL - 84
SP - 3379
EP - 3395
JO - Magnetic Resonance in Medicine
JF - Magnetic Resonance in Medicine
IS - 6
ER -