The Novel High-accuracy Impedance Tomography Enabled By The Time-of-flight EIT Via CHIRP Current Excitation (CHIRP-EIT)

目前还没有一种技术能够以足够的空间和时间分辨率对大脑的功能活动进行非侵入性成像。此外，还需要一种快速、精确和便携的成像技术，用于各种医疗应用，从中风到急性呼吸窘迫综合征（ARDS）等病症，救护车后面的快速成像可以挽救生命，以及许多其他急性病症，这些病症的治疗可以通过床边连续成像系统大大改善。传统的电阻抗断层扫描（EIT）通过将电极阵列（通常为32个）放置在感兴趣的物体（例如人的头部）周围，产生受试者内部电阻抗的图像。每次在一对电极之间注入难以察觉的、非常低幅度的已知电流，同时在其余电极上测量电势。通过在可能的电极对之间快速切换电流注入，可以进行多次测量，然后可以将其重建为内部电导率图像，其正常值的变化表明各种病理（例如中风）。EIT有可能成为一种实现快速便携和低成本成像解决方案的技术，但由于严重的理论限制，传统上它会导致图像质量差的模糊。飞行时间EIT可以克服所有的限制，极大地提高空间分辨率，理论上可以提供毫秒级时间分辨率的mri质量图像。该理论基于这样一个事实：如果电流以理想阶跃函数的形式注入，在导电物体内部，电流会扩散，不同的路径到达相反的电极需要不同的时间。通过测量不同到达时间的电压，可以区分上述所有不同路径的电导率，理论上这将产生清晰的高分辨率图像。虽然该技术在理论上是可行的，但在实践中它从未被执行过，因为它不可能产生电流的理想脉冲δ函数，并且在复杂的导电物体内存在与波传播相关的额外畸变。上述挑战可以通过采用暂时分离的CHIRP激励模式（线性调频）来解决。这种注入电流的方式在实践中是可能产生的，更重要的是，将允许分离真实到达时间和物体内部的所有扭曲。初步计算表明，这些CHIRP脉冲将使生成的图像具有1毫米的空间分辨率和1毫秒的时间分辨率。这将建立一种具有独特功能的全新成像技术，它有可能彻底改变诊断医学，并在医疗实践的几个领域进行挽救生命的改变。特别是，这将破坏神经学，因为没有其他技术可以在人脑内部进行非侵入性成像。

There is currently no technique that can non-invasively image the functional activity in the brain with sufficient spatial and temporal resolution. In addition, there is a need to have a rapid, precise and portable imaging technique for a variety of medical applications spanning from stroke, where rapid imaging on the back of an ambulance can be life-saving, to conditions like acute respiratory distress syndrome (ARDS) along with a multitude of other acute conditions, treatment of which could be greatly improved with having bedside continuous imaging system.The traditional Electrical Impedance Tomography (EIT) produces images of the internal electrical impedance of a subject using arrays of electrodes (usually 32) placed around the object of interest (e.g. human head). Imperceptible, very low amplitude known current is injected between a pair of electrodes at a time, while electric potentials are measured on the remaining electrodes. By rapid switching of current injections between the possible pairs of electrodes, multiple measurements are made which then can be reconstructed into the image of internal conductivity, the variations of which from the normal values are indicative of various pathologies (e.g. stroke). EIT could potentially be the technique enabling rapid portable and low-cost imaging solutions, but traditionally it results in poor quality blurry images because of the severe theoretical limitations.Time-of-flight EIT can overcome all limitations and result in great improvement in spatial resolution, theoretically providing MRI-quality images with millisecond temporal resolution. The theory relies on the fact that if the current is injected in form of an ideal step function, within the conductive object the current spreads and different paths would take different times to arrive at an opposite electrode. By measuring the voltages at different times of arrival, it is possible to distinguish between the conductivities of all the above different paths, which theoretically will result in a clear high-resolution image. Although the technique is theoretically possible, in practice it was never performed because it is impossible to produce an ideal pulse delta function of a current, and there are additional distortions associated with wave propagation inside the complex conductive object. The above challenges could be solved by employing temporally separated CHIRP excitation patterns (linear frequency modulation). This way of injecting the current is possible to produce in practice, and more importantly, would allow separation between the true time of arrival and all internal distortions within the object. Preliminary calculations showed that these CHIRP pulses would allow resulting images to have 1mm spatial resolution and 1 ms temporal resolution.This will establish a completely new imaging technique with unique capabilities, which has the potential to revolutionise diagnostic medicine and perform life-saving changes in several areas of medical practice. In particular, this will disrupt neurology where there are no other alternative techniques for non-invasive imaging inside the human brain.