Review of photoacoustic imaging for microrobots tracking in vivo

Fig.1 Schematic summary of photoacoustic imaging for microrobots tracking in vivo.

Scientists have invented microrobots that can directly reach the site of disease to perform medical tasks. Microrobots-assisted in vivo drug delivery, release, and in situ surgery are therefore seen as very promising medical solutions. In recent years, more researchers are focusing on how microrobots can be truly applied for clinical therapy. Many in vivo experiments on small animals have also been carried out to validate and advance the in vivo application of the microrobots.

At present, one of the biggest challenges in extending microrobots to the clinic is still the in vivo tracking. Among many biomedical imaging methods, photoacoustic imaging (PAI) is showing its outstanding advantages in the microrobots imaging in vivo. PAI combines the contrast of optical absorption with the spatial resolution of ultrasound for deep imaging in the tissue. The resolution of PAI ranges from several to a hundred micrometers for imaging in the millimeter- to centimeter-depth tissue. Briefly, the greatest advantage of PAI is its ability of label-free imaging across scales, from several to hundreds of microns, from microscopic to macroscopic, from cell nuclei to human organs. Different from the tissue and body fluids, microrobots covered with metallic materials have strong absorption of light and produce a strong photoacoustic signal for high-contrast, high-resolution imaging, which provides a solid basis for in vivo photoacoustic tracking of the microrobots.

PAI is a new hybrid imaging technique arising from the photoacoustic effect, which is based on the target's intrinsic absorption property. The principle is that when the tissue is shone by the pulsed laser beam, the target will absorb the light and generate instantaneous heat. The heat will cause thermal expansion and generate mechanical ultrasonic wave as the photoacoustic wave. After collecting the photoacoustic wave by ultrasonic transducer and reconstructing the signals, an image reflecting the light absorption distribution in biological tissue can be required, Figure 1 is a schematic diagram of photoacoustic imaging used for in-vivo tracking of micro-robots.

The research group led by Prof. Lidai Wang and Prof. Dong Sun from City University of Hong Kong summarized the PAI techniques, imaging systems, and their biomedical applications in microrobots tracking in vitro and in vivo. From a robotic tracking perspective, some insight into the future of PAI technology in clinical applications is provided. This review is published in Chinese Optics Letters, Volume 19, No. 11, 2021 (D. Li, et al., Review of photoacoustic imaging for microrobots tracking in vivo [Invited]).

Multiscale PAI enables tracking imaging of microrobots with different sizes for different targets. In this review, the PAI systems of photoacoustic computed tomography (PACT), optical-resolution photoacoustic microscopy (OR-PAM), and fast-scanning OR-PAM are highlighted and demonstrated from the perspective of microrobots tracking.

PACT is a reconstruction-based imaging method in photoacoustic imaging fields. PACT system adopts a wide-field illumination scheme to cover the tissue and collects the generated acoustic signals from spatially distributed sensors. The sensors array can be arranged in different layout in three-dimensional space to achieve a wider field of view detection and video-rate imaging speed, such as linear array, curved array, hemispherical array or planar array. Because of the diffused photons excitation and array-based computing reconstruction, PACT can achieve much deeper imaging depth than PAM imaging.

PACT with advantages in deep imaging and video-rate imaging speed can be used for whole-body dynamics and function imaging for small animals. Therefore, for real-time microrobots tracking in the deep tissue of the living body, PACT would be the best option. However, the limited resolution makes it difficult to track an individual microrobot less than 100 µm.

At this point, the OR-PAM compensates well for this deficiency, as its resolution can reach below 10 µm. For the high-resolution microrobots tracking in epidermal blood vessels or tissue, OR-PAM could be used as a priority. The OR-PAM can realize both subcellular multifunctional and robotic imaging, which provides a microscopic view for micro-robotic research. Finally, the polygon-scanning fast OR-PAM also demonstrates fast imaging capabilities, providing an excellent option for high-resolution real-time imaging for microrobots tracking.

For the time being, the most efficient way of driving robots in the living body is magnetic actuation. The integration of a robotic magnetic actuation system with the photoacoustic imaging system will take the future of robotic clinical applications to new heights.

In conclusion, photoacoustic imaging provides a comprehensive and superior biomedical imaging modality for microrobots navigation in living bodies. Future advances in photoacoustic imaging technology and the use of photoacoustic imaging in clinical applications will greatly facilitate the realization of robot-assisted medicine.

封面|光声成像技术在体内追踪微型机器人中的应用

图 1 用于体内跟踪微型机器人的光声成像示意图。

香港城市大学王立代和孙东教授课题组总结了光声成像技术、成像系统及其在体外和体内微型机器人追踪中的生物医学应用，并从机器人追踪的角度，对光声成像技术在临床应用中的前景进行了展望。相关成果发表在Chinese Optics Letters 2021年第19卷第11期上(D. Li, et al., Review of photoacoustic imaging for microrobots tracking in vivo [Invited])。

临床微型机器人

临床微型机器人能够辅助体内药物输送、释放和进行原位手术，其直达病灶并进行治疗的优势被视为非常有应用前景的医疗解决方案。近年来，越来越多的研究人员关注如何将微型机器人真正应用于临床治疗，许多小动物的体内实验也已相继展开，用以验证和推进微型机器人在体内的应用。

光声成像

光声成像是一种基于光声效应和目标内在吸收特性的混合成像技术。其原理是，当组织被脉冲激光束照射时，目标会吸收光线并产生瞬时热量。热量将导致热膨胀并产生机械超声波作为光声波。在用超声波传感器收集光声波并重建信号后，可以得到反映生物组织中光吸收分布的图像。

光声成像在深层组织成像方面，融合了光吸收的对比度和超声的空间分辨率的优势。其分辨率从几微米到几百微米，可用于在毫米到厘米深度的组织中成像。简而言之，光声成像的最大优势是它能够在不同尺度上进行无标记物成像，从几微米到数百微米，从微观到宏观，从细胞核到人体器官。

光声成像微型机器人

目前，体内追踪仍是微型机器人推广到临床应用的一大挑战。在众多生物医学成像方法中，光声成像微型机器人在体内成像中正显示出其突出的优势。镀金属的微型机器人与组织和体液不同，其对光有很强的吸收能力，能够产生强烈的光声信号，可以进行高对比度、高分辨率的成像，这为微型机器人实现在体内光声跟踪提供了坚实的基础，图1为用于体内跟踪微型机器人的光声成像示意图。

多尺度光声成像

多尺度光声成像能够对不同目标和尺寸的微型机器人进行跟踪成像。王立代教授课题组从微型机器人跟踪的角度出发，对光声计算机断层扫描成像（PACT）、光学分辨率光声显微成像（OR-PAM）和快速扫描OR-PAM成像进行了系统地总结和展望。

PACT是光声成像领域中一种基于重建的成像方法。PACT系统采用宽视场照明方案来覆盖组织，并从空间分布的传感器收集产生的声学信号。传感器阵列可以在三维空间中进行不同的布局，以实现更宽的视野检测和视频速率的成像速度，如线性阵列、弧形阵列、半球形阵列或平面阵列。由于采用了扩散光子激发和基于阵列的计算重建，PACT可以实现比PAM成像更深的成像深度。

PACT具有深度成像和视频级成像速度的优势，可用于小动物全身动态和功能成像。因此，在活体深层组织的实时微型机器人追踪中，PACT将是最佳选择。然而，有限的分辨率使其难以跟踪直径小于100 μm的单个微型机器人。而OR-PAM分辨率可以达到10 μm以下，很好地弥补了这一不足。对于表皮血管或组织中的高分辨率微型机器人追踪，可以优先使用OR-PAM。OR-PAM可以同时实现亚细胞多功能和机器人成像，这为微型机器人的研究提供了微观视角。此外，快速OR-PAM也展示了快速成像能力，为微型机器人跟踪的高分辨率实时成像提供了一个很好的选择。

未来展望

如今，磁驱动是在活体中驱动机器人最有效的方式。将磁驱动系统与光声成像系统相结合把机器人临床应用推向了新的高度。光声成像也为微型机器人在活体中的追踪提供了一种全面而优越的生物医学成像方式。未来光声成像技术的发展和光声成像在临床应用中的应用将大大促进机器人辅助医疗的实现。