Multifactorial Analysis of MRI Gradient Safety for Active Implantable Medical Devices: Coil Design, Implant Trajectories, and Scan Configurations.

IF 3.4 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Xu Boya, Changqing Jiang, Peishan Li, Wanxuan Sang, Luming Li
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Abstract

Objective: Electromagnetic (EM) modelling is an effective method for evaluating the gradient safety of magnetic resonance imaging (MRI) for patients with active implantable medical devices (AIMDs). However, the combined effects of multiple factors-including gradient coil design constraints, implanted lead path, gradient strength, and scan configuration-on gradient-induced voltage (GIV) risk has not been systematically investigated. In particular, the magnetic field distribution outside the region of linearity (ROL) of gradient coils cannot be uniquely determined from their nominal gradient profile, and its impact on AIMD gradient safety assessment remains poorly understood.

Approach: This study presents a multifactorial analysis of MRI gradient safety by integrating gradient coil modelling with anatomical lead path tracing using a reference human body shell. We examine how variations in coil design constraints affect magnetic field distributions and how these, in turn, influence GIV for three representative AIMDs' pathways: deep brain stimulators (DBS), cardiac pacemakers (PM), and sacral nerve stimulators (SNM). Multiple gradient strengths, coil excitation modes, and scanning positions are assessed.

Results: Magnetic field distributions vary significantly between coil designs, particularly in the concomitant Bx and By components, with differences reaching up to 53%. These variations result in GIV difference that increases with gradient strength. The maximum GIV differences for DBS, SNM, and PM reach 1.08V, 0.52V, and 0.93V, respectively, under Y-axis excitation. The concomitant field plays a significant role in these differences. Simultaneous excitation of all axes does not always produce the highest GIV due to cancellation effects. Cross-AIMD analysis shows high-risk zones are concentrated in and around the ROL.

Significance: This work fills a gap by systematically evaluating how coil design, implant characteristics, gradient strength, and scan configurations influence GIV risk, providing a foundation for more comprehensive, individualized MRI gradient safety assessments.

主动植入医疗器械的MRI梯度安全性的多因素分析:线圈设计,植入物轨迹和扫描配置。
目的:电磁(EM)建模是评估有源植入式医疗器械(AIMDs)患者磁共振成像(MRI)梯度安全性的有效方法。然而,包括梯度线圈设计约束、植入引线路径、梯度强度和扫描配置在内的多种因素对梯度感应电压(GIV)风险的综合影响尚未得到系统的研究。特别是,梯度线圈线性区(ROL)外的磁场分布不能从其标称梯度曲线中唯一地确定,其对AIMD梯度安全性评估的影响仍然知之甚少。方法:本研究通过将梯度线圈建模与参考人体外壳的解剖引线路径追踪相结合,提出了MRI梯度安全性的多因素分析。我们研究线圈设计约束的变化如何影响磁场分布,以及磁场分布如何反过来影响三种代表性aimd通路的GIV:深部脑刺激器(DBS)、心脏起搏器(PM)和骶神经刺激器(SNM)。多重梯度强度,线圈激励模式,和扫描位置进行评估。结果:线圈设计之间的磁场分布差异很大,特别是伴随的Bx和By组件,差异可达53%。这些变化导致梯度梯度差随着梯度强度的增大而增大。在y轴激励下,DBS、SNM和PM的最大GIV差异分别达到1.08V、0.52V和0.93V。伴随场在这些差异中起着重要作用。由于抵消效应,所有轴的同时激励并不总是产生最高的给力。交叉目标分析显示,高风险区域集中在ROL及其周围。意义:本研究通过系统评估线圈设计、植入物特征、梯度强度和扫描配置对GIV风险的影响,填补了这一空白,为更全面、个性化的MRI梯度安全性评估提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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