基于$B_{1}^+$的脑受试者特异性SAR图的电学性质层析成像评价和校正

IF 3 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2023-02-14 DOI:10.1109/JERM.2023.3236153
Jessica A. Martinez;Alessandro Arduino;Oriano Bottauscio;Luca Zilberti
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引用次数: 0

摘要

比吸收率(SAR)估计组织吸收的功率量,并由电导率和电场确定。电导率可以使用电学性质层析成像(EPT)来估计,但只有与$B_{1}^+$相关的电场分量可以从$B_{1]$映射中推导出来。在此,计算了一个校正因子,以补偿实际SAR与用$B_{1}^+$获得的SAR之间的差异。对27个水头模型进行了128美元的数值模拟。使用精确的电导率和E场计算地面实况局部SAR和10g SAR(SARGT)。使用对流反应EPT获得的电导率和从$B_{1}^+$获得的E场来计算估计的局部SAR和10g SAR(SAREST)。估计灰质、白质和脑脊液的校正因子(CF)。对不同水平的信噪比(SNR)进行了比较。灰质的局部SAR/10g CF为3.08$\pm$0/06/2.11$\pm0.04,白质为1.79$\pm$0/05/2.06$\pm=0.04,CSF为2.59$\pm$0/05/1.95$\pm0.03。没有CF的严重急性呼吸系统综合征被低估了([$\infty$-25]SNRs的比率:0.52$\pm$0.02(当地严重急性呼吸综合征);0.55$\pm$0.01(10g严重急性呼吸复合征)。校正后,严重急性呼吸系统综合征等效于严重急性呼吸综合征综合征(【$\infty$-25】SNRs的比率:当地SAR为0.97$\pm$0.02;10g SAR为1.06$\pm$0.01)。基于$B_{1}^+$的SAR图可以用校正因子进行校正,以补偿实际SAR和用从$B_{1}^+$导出的E场计算的SAR之间的潜在差异。
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Evaluation and Correction of $B_{1}^+$-Based Brain Subject-Specific SAR Maps Using Electrical Properties Tomography
The specific absorption rate (SAR) estimates the amount of power absorbed by the tissue and is determined by the electrical conductivity and the E-field. Conductivity can be estimated using Electric Properties Tomography (EPT) but only the E-field component associated with $B_{1}^+$ can be deduced from $B_{1}$ -mapping. Herein, a correction factor was calculated to compensate for the differences between the actual SAR and the one obtained with $B_{1}^+$ . Numerical simulations were performed for 27 head models at $128 \,\mathrm{M}\mathrm{Hz}$ . Ground-truth local-SAR and 10g-SAR (SAR GT ) were computed using the exact electrical conductivity and the E-field. Estimated local-SAR and 10g-SAR (SAR EST ) were computed using the electrical conductivity obtained with a convection-reaction EPT and the E-field obtained from $B_{1}^+$ . Correction factors (CFs) were estimated for gray matter, white matter, and cerebrospinal fluid (CSF). A comparison was performed for different levels of signal-to-noise ratios (SNR). Local-SAR/10g-SAR CF was 3.08 $\pm$ 0/06 / 2.11 $\pm$ 0.04 for gray matter, 1.79 $\pm$ 0/05 / 2.06 $\pm$ 0.04 for white matter, and 2.59 $\pm$ 0/05 / 1.95 $\pm$ 0.03 for CSF. SAR EST without CF were underestimated (ratio across [ $\infty$ - 25] SNRs: 0.52 $\pm$ 0.02 for local-SAR; 0.55 $\pm$ 0.01 for 10g-SAR). After correction, SAR EST was equivalent to SAR GT (ratio across [ $\infty$ - 25] SNRs: 0.97 $\pm$ 0.02 for local-SAR; 1.06 $\pm$ 0.01 for 10g-SAR). SAR maps based on $B_{1}^+$ can be corrected with a correction factor to compensate for potential differences between the actual SAR and the SAR calculated with the E-field derived from $B_{1}^+$ .
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Front Cover Table of Contents IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information Models of Melanoma Growth for Assessment of Microwave-Based Diagnostic Tools
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