Ma Jieshi, Guo Jie, Li Yang, Wang Zheng, Dong Yunpeng, Ma Jianxing, Zhu Yan, Wu Guan, Yi Liang, Shi Xuetao
Department of Medical Engineering, Army Medical Center of PLA, Chongqing, China.
Institute of Medical Research, Northwestern Polytechnical University, Xi'an, China.
Front Neurol. 2023 Aug 11;14:1210991. doi: 10.3389/fneur.2023.1210991. eCollection 2023.
The purpose of this paper is to compare the differences in the features of multifrequency electrical impedance tomography (MFEIT) images of human heads between healthy subjects and patients with brain diseases and to explore the possibility of applying MFEIT to intracranial abnormality detection.
Sixteen healthy volunteers and 8 patients with brain diseases were recruited as subjects, and the cerebral MFEIT data of 9 frequencies in the range of 21 kHz - 100 kHz of all subjects were acquired with an MFEIT system. MFEIT image sequences were obtained according to certain imaging algorithms, and the area ratio of the ROI (AR_ROI) and the mean value of the reconstructed resistivity change of the ROI (MVRRC_ROI) on both the left and right sides of these images were extracted. The geometric asymmetry index (GAI) and intensity asymmetry index (IAI) were further proposed to characterize the symmetry of MFEIT images based on the extracted indices and to statistically compare and analyze the differences between the two groups of subjects on MFEIT images.
There were no significant differences in either the AR_ROI or the MVRRC_ROI between the two sides of the brains of healthy volunteers ( > 0.05); some of the MFEIT images mainly in the range of 30 kHz - 60 kHz of patients with brain diseases showed stronger resistivity distributions (larger area or stronger signal) that were approximately symmetric with the location of the lesions. However, statistical analysis showed that the AR_ROI and the MVRRC_ROI on the healthy sides of MFEIT images of patients with unilateral brain disease were not significantly different from those on the affected side ( > 0.05). The GAI and IAI were higher in all patients with brain diseases than in healthy volunteers except for 80 kHz ( < 0.05).
There were significant differences in the geometric symmetry and the signal intensity symmetry of the reconstructed targets in the MFEIT images between healthy volunteers and patients with brain diseases, and the above findings provide a reference for the rapid detection of intracranial abnormalities using MFEIT images and may provide a basis for further exploration of MFEIT for the detection of brain diseases.
本文旨在比较健康受试者与脑部疾病患者头部多频电阻抗断层成像（MFEIT）图像特征的差异，并探讨MFEIT应用于颅内异常检测的可能性。
招募16名健康志愿者和8名脑部疾病患者作为研究对象，使用MFEIT系统采集所有受试者在21kHz - 100kHz范围内9个频率的脑部MFEIT数据。根据特定成像算法获得MFEIT图像序列，并提取这些图像左右两侧感兴趣区域的面积比（AR_ROI）和感兴趣区域重建电阻率变化的平均值（MVRRC_ROI）。基于提取的指标进一步提出几何不对称指数（GAI）和强度不对称指数（IAI）来表征MFEIT图像的对称性，并对两组受试者MFEIT图像的差异进行统计学比较和分析。
健康志愿者脑部两侧的AR_ROI和MVRRC_ROI均无显著差异（>0.05）；部分脑部疾病患者主要在30kHz - 60kHz范围内的一些MFEIT图像显示出较强的电阻率分布（面积较大或信号较强），且与病变位置大致对称。然而，统计分析表明，单侧脑部疾病患者MFEIT图像健康侧的AR_ROI和MVRRC_ROI与患侧无显著差异（>0.05）。除80kHz外，所有脑部疾病患者的GAI和IAI均高于健康志愿者（<0.05）。
健康志愿者与脑部疾病患者的MFEIT图像中重建目标的几何对称性和信号强度对称性存在显著差异，上述研究结果为利用MFEIT图像快速检测颅内异常提供了参考，也可能为进一步探索MFEIT用于脑部疾病检测提供依据。
