首页> 外文会议>IEEE-EMBS Conference on Biomedical Engineering and Sciences >Functional MRI of neuro-electro-magnetic oscillations: Statistical processing in the presence of system imperfections
【24h】

Functional MRI of neuro-electro-magnetic oscillations: Statistical processing in the presence of system imperfections

机译:神经电磁振荡的功能MRI:系统缺陷存在下的统计处理

获取原文

摘要

Direct detection of magnetic fields elicited by neuronal activity using Magnetic Resonance Imaging (MRI) has been a long standing research goal, due to its potential to overcome limitations that are inherent to BOLD fMRI. The MRI signal can be sensitized to oscillating magnetic fields using spin-lock preparations. However, the susceptibility of spin-lock sequences to system imperfections has so far hindered their translational potential for in vivo experiments. Moreover, the sensitivity of the neuro-current MRI signal to the phase of neuro-electric oscillations generates high variance time courses that are not suited for analysis with traditional fMRI data processing techniques. In this work we study the impact of various MRI system imperfections on neuro-current MRI in simulations. Furthermore we propose Statistical Variance Mapping (SVarM) as a new data processing technique for generating activity maps from neuro-current MRI signal variance. Bloch simulations demonstrated substantial variations of signal intensity for a 400 Hz range of off-resonances and a 360° range of neuro-current oscillating phases. SVarM was tested on synthetic neuro-current data simulated with various degrees of system imperfections. The proposed technique was compared to the previously developed NEMO processing, which is based on mean analysis of time courses. Simulation results show improved resilience against Bo inhomogeneities with SVarM compared with NEMO processing (Dice coefficient of activation maps: 64.07% SVarM, 57.76% NEMO, $mathrm{p} < 0.02$). Comparable or slightly improved robustness against $mathrm{B}_{1}^{+}$ inhomogeneities was observed as well as higher sensitivity in the absence of $mathrm{B}_{1}^{+}$ inhomogeneities (Dice score of activation maps: 58.34% SVarM, 49.70% NEMO, $mathrm{p} < 0.01$). Finally, SVarM achieved better specificity for low SNR, resulting in activation maps with fewer false positive voxels (FP rate: 0.53% SVarM, 19.28% NEMO, $mathrm{p} < 0.01$). These results underscore the importance of dedicated data processing methods and robust pulse sequences to facilitate the widespread use of direct neuro-current MRI in the presence of system imperfections.
机译:通过使用磁共振成像(MRI)引起神经元活动引起的磁场的直接检测是长期的研究目标,因为它可能克服了粗体FMRI所固有的限制。 MRI信号可以使用旋转锁定制剂敏感到振荡磁场。然而,旋转锁定序列对系统缺陷的敏感性迄今为止已经阻碍了他们在体内实验中的平移潜力。此外,神经电流MRI信号对神经电振荡相的敏感性产生高方差时间课程,其不适合通过传统的FMRI数据处理技术进行分析。在这项工作中,我们研究了各种MRI系统缺陷对仿真内神经电流MRI的影响。此外,我们提出了统计方差映射(SVARM)作为一种新的数据处理技术,用于从神经电流MRI信号方差产生活动映射。 Bloch模拟显示了400Hz偏离共振范围的信号强度和360°的神经电流振荡阶段的大量变化。 SVARM对具有各种系统缺陷的合成神经电流数据进行了测试。将所提出的技术与先前开发的NEMO处理进行了比较,这是基于时间课程的平均分析。仿真结果表明,与NEMO加工相比,仿真结果对具有SVARM的BO不均匀性(骰子系数地图:64.07%SVARM,57.76%Nemo, $ mathrm {p} < 0.02 $ )。可比或略微改善鲁棒性 $ mathrm {b} _ {1} ^ {+} $ 观察到不均匀性以及缺乏较高的敏感性 $ mathrm {b} _ {1} ^ {+} $ 不均匀性(骰子激活地图:58.34%SVARM,49.70%Nemo, $ mathrm {p} < 0.01 $ )。最后,Svarm对低SNR实现了更好的特异性,导致具有较少误毒素的激活图(FP率:0.53%SVARM,19.28%Nemo, $ mathrm {p} < 0.01 $ )。这些结果强调了专用数据处理方法和鲁棒脉冲序列的重要性,以便于在系统缺陷存在下广泛使用直接神经电流MRI。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号