Electric field calculation and peripheral nerve stimulation prediction for head and body gradient coils

被引:8
|
作者
Roemer, Peter B. [1 ]
Wade, Trevor [2 ]
Alejski, Andrew [2 ]
McKenzie, Charles A. [3 ]
Rutt, Brian K. [4 ]
机构
[1] Roemer Consulting, Lutz, FL USA
[2] Robarts Res Inst London, Imaging Res Labs, London, ON, Canada
[3] Western Univ, Dept Med Biophys, London, ON, Canada
[4] Stanford Univ, Dept Radiol, 1201 Welch Rd, Stanford, CA 94305 USA
基金
美国国家卫生研究院;
关键词
asymmetric and symmetric gradient; E-field; electric field; gradient coil; head gradient; peripheral nerve stimulation; PNS; MAGNETIC STIMULATION; MRI; OPTIMIZATION;
D O I
10.1002/mrm.28853
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To demonstrate and validate electric field (E-field) calculation and peripheral nerve stimulation (PNS) prediction methods that are accurate, computationally efficient, and that could be used to inform regulatory standards. Methods: We describe a simplified method for calculating the spatial distribution of induced E-field over the volume of a body model given a gradient coil vector potential field. The method is easily programmed without finite element or finite difference software, allowing for straightforward and computationally efficient E-field evaluation. Using these E-field calculations and a range of body models, population-weighted PNS thresholds are determined using established methods and compared against published experimental PNS data for two head gradient coils and one body gradient coil. Results: A head-gradient-appropriate chronaxie value of 669 mu s was determined by meta-analysis. Prediction errors between our calculated PNS parameters and the corresponding experimentally measured values were similar to 5% for the body gradient and similar to 20% for the symmetric head gradient. Our calculated PNS parameters matched experimental measurements to within experimental uncertainty for 73% Delta G(min) estimates and 80% of SRmin estimates. Computation time is seconds for initial E-field maps and milliseconds for E-field updates for different gradient designs, allowing for highly efficient iterative optimization of gradient designs and enabling new dimensions in PNS-optimal gradient design. Conclusions: We have developed accurate and computationally efficient methods for prospectively determining PNS limits, with specific application to head gradient coils.
引用
收藏
页码:2301 / 2315
页数:15
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