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用于评估肌肉健康的电阻抗断层成像与超声成像的结合。

Toward Electrical Impedance Tomography Coupled Ultrasound Imaging for Assessing Muscle Health.

出版信息

IEEE Trans Med Imaging. 2019 Jun;38(6):1409-1419. doi: 10.1109/TMI.2018.2886152. Epub 2018 Dec 10.

Abstract

This paper establishes for the first time that a coupled ultrasound (US) and electrical impedance tomography (EIT) system can serve as a non-invasive, spatially localized approach to extract clinically relevant muscle properties. The US/EIT system represents a potential enhancement to electrical impedance myography (EIM), which has shown promise as a non-invasive technology that may have important clinical use in indicating neuromuscular disease status and as a diagnostic tool. A 2.5D EIT algorithm evaluated on simulation, measured phantoms, and measured patient data was studied to evaluate US/EIT's ability to distinguish different aspects of muscle tissue. Simulated and phantom experiments revealed the depths of distinguishability of 3.2 and 4.2 mm in simulation for 10% and 20% changes in muscle properties, respectively, and 3.6 mm in measured phantom experiments assuming a 12% muscle conductivity change. Reconstructions from the patient data established that there were consistent differences 1) between longitudinal (along) and transverse (across) muscle conductivity reconstructions at frequencies of 40 and 80 kHz and 2) side-by-side comparison between healthy and diseased tissue in terms of conductivity, permittivity, and phase at 40 and 80 kHz. Comparisons were made between the EIT reconstructed values and electrical impedance spectroscopy (EIS) measurements (an available surrogate in place of standard EIM measurements) made with the US/EIT system, wherein 1) EIS and EIT show similar sensitivity to longitudinal and transverse differences and 2) EIT showed a more consistent ability to differentiate healthy and diseased tissue. These results suggest that US/EIT appears very promising for non-invasive and spatially localized diagnosis of muscle health.

摘要

本文首次建立了一个超声(US)和电阻抗断层成像(EIT)系统相结合的方法,该方法可以作为一种非侵入性、空间局部化的方法,提取具有临床相关性的肌肉特性。US/EIT 系统代表了一种增强型的电阻抗肌图(EIM),它作为一种非侵入性技术具有很大的潜力,可能在指示神经肌肉疾病状态和作为诊断工具方面具有重要的临床应用。本文研究了一种基于 2.5D 模型的 EIT 算法,该算法基于模拟、测量的体模和测量的患者数据进行了评估,以评估 US/EIT 区分不同肌肉组织方面的能力。模拟和体模实验揭示了在模拟中,10%和 20%的肌肉特性变化时,US/EIT 分别能区分 3.2 和 4.2 毫米的深度,而在测量的体模实验中,假设肌肉电导率变化 12%,则能区分 3.6 毫米的深度。患者数据的重建结果表明,在 40 和 80 kHz 频率下,1)纵向(沿)和横向(横)肌肉电导率重建之间存在一致的差异,2)在 40 和 80 kHz 时,健康组织和病变组织之间在电导率、介电常数和相位方面存在一致的差异。本文还将 EIT 重建值与 US/EIT 系统进行的电阻抗谱(EIS)测量(可用作标准 EIM 测量的替代物)进行了比较,其中 1)EIS 和 EIT 对纵向和横向差异具有相似的敏感性,2)EIT 显示出更好的区分健康和病变组织的能力。这些结果表明,US/EIT 非常有希望用于肌肉健康的非侵入性和空间局部化诊断。

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本文引用的文献

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NOSER: An Algorithm for Solving the Inverse Conductivity Problem.NOSER:一种求解电导率反问题的算法。
Int J Imaging Syst Technol. 1990 Summer;2(2):66-75. doi: 10.1002/ima.1850020203.
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