Evaluation of Sensor and Analysis Area in the Signal Source Estimation by Spatial Filter for Magnetocardiography
Evaluation of Sensor and Analysis Area in the Signal Source Estimation by Spatial Filter for Magnetocardiography
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DOI：
10.1109/tmag.2021.3083329
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发表时间：
2022-09
影响因子：
2.1
通讯作者：
M. Iwai;Narita Seihou;Koichiro Kobayashi;W. Sun
中科院分区：
文献类型：
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作者：
M. Iwai;Narita Seihou;Koichiro Kobayashi;W. Sun
心磁图（MCG）在各种临床研究中被广泛研究和评价，以发现心脏疾病的早期阶段。特别地，期望建立能够提供关于心脏的病变部位的详细信息的技术。目前的空间滤波方法，如精确低分辨率脑电磁断层成像（eLORETA）的估计结果包含误差，并且对于临床应用来说估计精度不足。位于端部的传感器的信息不能被利用，并且影响估计结果的信息量对于每个传感器是不同的，这导致有偏估计解的导出。因此，在本研究中，我们认为可以通过设置大于传感器面积的分析区域来均等地使用每个传感器的信息量，并提出了一种关注信号源估计的分析区域与传感器平面之间的关系的方法。我们模拟了要使用的最有效和最优化的分析区域，并使用在剑突正上方调整51 ch传感器时使用的实际MCG的QRS波群峰值数据，通过eLORETA进行源信号估计。我们比较了以下三种分析区域尺寸：$x = 120 $mm，$y = 120 $mm，$z = 100 $mm（a）;$x = 180 $mm，$y = 180 $mm，$z = 100 $mm（B）;$x = 240 $mm，$y = 240 $mm，$z = 100 $mm（c）。因此，由于来自心脏的信号最初被认为是单个块，因此估计的解也预计是单个块。将溶液作为单个区组进行估计，分析区域（a）的情况除外，其对应于常规方法。另外，估计解的位置和大小与从计算机断层摄影（CT）图像获得的心脏的位置和大小相似。各分析区域的拟合优度约为0.99或更大，这表明没有显著差异。因此，我们证明了通过估计MCG的时间序列波形来可视化心肌的运动是可能的。
Magnetocardiography (MCG) has been extensively investigated and evaluated in various clinical studies for its potential in detecting the early stages of cardiac diseases. In particular, the establishment of a technology that can provide detailed information on the lesion parts of the heart is expected. The estimation result of the current spatial filter method, such as the exact low-resolution brain electromagnetic tomography (eLORETA), contains errors and has insufficient estimation accuracy for clinical applications. The information of sensors located at the ends cannot be utilized, and the amount of information that affects the estimation result is different for each sensor, which causes the derivation of a biased estimated solution. Therefore, in this study, we considered that the amount of information of each sensor can be used equally by setting an analysis area larger than the sensor area and proposed a method focusing on the relationship between the analysis area of signal source estimation and the sensor plane. We simulated the most efficient and optimized analysis area to be used and performed the source signal estimation by eLORETA using the QRS-complex peak data of the actual MCGs used in adjusting the 51ch sensor directly above the xiphoid process. We compared the following three sizes of the analysis area: $x =120$ mm, $y =120$ mm, and $z =100$ mm (a); $x =180$ mm, $y =180$ mm, and $z =100$ mm (b); and $x =240$ mm, $y =240$ mm, $z =100$ mm (c). Thus, because the signals from the heart are originally considered to be a single block, the estimated solution is also expected to be a single block. The solution was estimated as a single block, except case with analysis area (a), which corresponds to the conventional method. In addition, the position and size of the estimated solution are similar to those of the heart obtained from the computed tomography (CT) images. The goodness of fit of each analysis area was approximately 0.99 or more, which indicated that there was no significant difference. Thus, we demonstrated that it is possible to visualize the movement of the myocardium by estimating the time-series waveform of the MCG.