Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography(EIT) is a f...Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography(EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies,which has led to its potential clinical use. This qualitative review provides an overview of the basic principles,algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy,stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth,from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry,inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.展开更多
Lorentz force electrical impedance tomography （LFEIT） combines ultrasound stimulation and electromagnetic field detection with the goal of creating a high contrast and high resolution hybrid imaging modality. In thi...Lorentz force electrical impedance tomography （LFEIT） combines ultrasound stimulation and electromagnetic field detection with the goal of creating a high contrast and high resolution hybrid imaging modality. In this study, pulse compression working together with a linearly frequency modulated ultrasound pulse was investigated in LFEIT. Experiments were done on agar phantoms having the same level of electrical conductivity as soft biological tissues. The results showed that：（i） LFEIT using pulse compression could detect the location of the electrical conductivity variations precisely; （ii） LFEIT using pulse compression could get the same performance of detecting electrical conductivity variations as the traditional LFEIT using high voltage narrow pulse but reduce the peak stimulating power to the transducer by 25.5 dB; （iii） axial resolution of 1 mm could be obtained using modulation frequency bandwidth 2 MHz.展开更多
目前常用的电阻抗断层成像(EIT)相邻激励-相邻测量模式下,有限测量分辨率(MR)和信噪比(SNR)的系统往往难于分辨微小电位差,影响图像重建。通过获取16电极EIT系统均匀场在相邻、间隔6电极和相对激励模式下的理想仿真边界电压,分析实用化...目前常用的电阻抗断层成像(EIT)相邻激励-相邻测量模式下,有限测量分辨率(MR)和信噪比(SNR)的系统往往难于分辨微小电位差,影响图像重建。通过获取16电极EIT系统均匀场在相邻、间隔6电极和相对激励模式下的理想仿真边界电压,分析实用化EIT系统成像对MR和SNR的要求,仿真模拟了不同MR和SNR测量条件下3种激励模式对近场域中心目标A、场域1/2半径处目标B、近场域边缘目标C的成像。图像重建采用Tikhonov-Noser组合正则化算法,引入图像重建误差函数和结构相似度函数定量评价成像效果。结果表明,各激励模式对不同目标成像要求的MR和SNR不同。MR为1 m V和0.01 m V时,成像效果分别是间隔6电极激励和相邻激励最优;MR为0.1 m V时对模型A、B成像间6激励更优,对模型C成像相邻激励更好。间隔6电极和相对激励对模型A、B、C成像要求的SNR临界值分别为50、40和30 d B,都比相邻激励低10 d B,临界值附近间6成像效果最优,其次是相对激励,SNR高于临界值10 d B时相邻激励成像质量最高。低MR和高MR时影响成像的主要指标分别是各模式边界电压次小值与最小值之差和独立测量数。建议低MR成像时优先选择间6激励,其次是相对激励,高MR时选择相邻激励,MR为0.1 m V时近场域边缘目标成像选择相邻激励而近场域中心目标成像选择间6激励。低SNR和高SNR时影响成像的是测量电压数组整体的数值大小和独立测量数。模型A、B、C成像时若SNR分别在50、40和30 d B的临界值附近建议选择间隔6电极和相对激励,一旦SNR高于临界值10 d B,建议选择相邻激励。展开更多
基金supported by the National Natural Science Foundation of China (81773353)Jilin Scientific and Technological Development Program (20200404148YY, 20200601005JC, 20210101317JC)+2 种基金Jilin Province Special Projec t of Medical and Health Talents (JLSCZD2019-032)the Research Funding Program of Norman Bethune Biomedical Engineering Center (BQEGCZX2019025)National College Students Innovation and Entrepreneurship Training Program (CN)(202010183691)。
文摘Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography(EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies,which has led to its potential clinical use. This qualitative review provides an overview of the basic principles,algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy,stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth,from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry,inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51137004 and 61427806)the Scientific Instrument and Equipment Development Project of Chinese Academy of Sciences(Grant No.YZ201507)the China Scholarship Council(Grant No.201604910849)
文摘Lorentz force electrical impedance tomography （LFEIT） combines ultrasound stimulation and electromagnetic field detection with the goal of creating a high contrast and high resolution hybrid imaging modality. In this study, pulse compression working together with a linearly frequency modulated ultrasound pulse was investigated in LFEIT. Experiments were done on agar phantoms having the same level of electrical conductivity as soft biological tissues. The results showed that：（i） LFEIT using pulse compression could detect the location of the electrical conductivity variations precisely; （ii） LFEIT using pulse compression could get the same performance of detecting electrical conductivity variations as the traditional LFEIT using high voltage narrow pulse but reduce the peak stimulating power to the transducer by 25.5 dB; （iii） axial resolution of 1 mm could be obtained using modulation frequency bandwidth 2 MHz.
文摘目前常用的电阻抗断层成像(EIT)相邻激励-相邻测量模式下,有限测量分辨率(MR)和信噪比(SNR)的系统往往难于分辨微小电位差,影响图像重建。通过获取16电极EIT系统均匀场在相邻、间隔6电极和相对激励模式下的理想仿真边界电压,分析实用化EIT系统成像对MR和SNR的要求,仿真模拟了不同MR和SNR测量条件下3种激励模式对近场域中心目标A、场域1/2半径处目标B、近场域边缘目标C的成像。图像重建采用Tikhonov-Noser组合正则化算法,引入图像重建误差函数和结构相似度函数定量评价成像效果。结果表明,各激励模式对不同目标成像要求的MR和SNR不同。MR为1 m V和0.01 m V时,成像效果分别是间隔6电极激励和相邻激励最优;MR为0.1 m V时对模型A、B成像间6激励更优,对模型C成像相邻激励更好。间隔6电极和相对激励对模型A、B、C成像要求的SNR临界值分别为50、40和30 d B,都比相邻激励低10 d B,临界值附近间6成像效果最优,其次是相对激励,SNR高于临界值10 d B时相邻激励成像质量最高。低MR和高MR时影响成像的主要指标分别是各模式边界电压次小值与最小值之差和独立测量数。建议低MR成像时优先选择间6激励,其次是相对激励,高MR时选择相邻激励,MR为0.1 m V时近场域边缘目标成像选择相邻激励而近场域中心目标成像选择间6激励。低SNR和高SNR时影响成像的是测量电压数组整体的数值大小和独立测量数。模型A、B、C成像时若SNR分别在50、40和30 d B的临界值附近建议选择间隔6电极和相对激励,一旦SNR高于临界值10 d B,建议选择相邻激励。
