Realtime high resolution 3D multispectral photoacoustic imaging

我的研究计划的长期目标是开发快照三维光声成像的高分辨率，多光谱，超快成像的生化和生物过程中高度混浊的介质，如人体组织。 快照3D光声成像有可能解决正常和患病组织（例如癌症）之间的差异，而无需冗长的扫描程序和对运动伪影的敏感性。 快照3D光声成像代表了一种混合技术，其中单个激光脉冲（5-10 ns）漫射照射介质。 作为响应，介质中的光学吸收体（目标）产生超声频率（0.2-10 MHz）的声波。 成像是通过用链接到数据采集硬件的超声换能器的固定阵列并行地检测和记录声波而产生的。 然后将光声记录重建成代表目标的位置、大小、形状和光学性质的图像。 快照3D光声成像的主要限制之一是图像质量差，特别是对于诸如生物组织中的光学吸收体的复杂目标。 差的图像质量是由于当前可用的换能器阵列和数据采集硬件导致的实际通道密度限制的结果。 即使是装备最好的光声研究小组也只能同时使用不超过256个检测通道。 因此，研究小组选择以牺牲快照能力为代价扫描换能器阵列，以有效地获得重建高质量图像所需的更高通道密度。 我的团队选择通过以下方式开发用于快照成像的固定阵列：（i）针对当前可用的通道密度优化换能器阵列设计，以获得与更高密度系统相当的质量的图像;（ii）客观地评估优化设计的成像性能;以及（iii）开发实际可靠地扩展到数千个通道的新技术。 为了实现这三个研究目标，研究计划将建立在我的小组开发的方法。 首先，我们计划使用串扰分析来设计、优化和测试换能器阵列。 串扰分析提供成像体积内的系统灵敏度的客观测量（独立于图像重建方法），并且还提供成像体积内从一个位置到另一个位置的换能器信号的混叠（重叠）的估计。 在整个图像体积中具有高灵敏度和低混叠的换能器阵列设计可以被认为是最佳设计。 其次，我们计划应用传统的图像质量评估技术，研究成像性能的换能器阵列设计使用信号保真度和感知的视觉质量指标。 将针对一系列成像任务估计图像质量指标，这些成像任务为每个优化设计提供几何复杂性增加的目标。 最后，我们将研究传统的方法，将现有的数据采集硬件扩展到数千个检测通道，并研究一种全新的基于光学的声换能器的灵敏度和带宽，该换能器有可能被制造成具有数千个独立检测通道的大型阵列。 如果我们成功了，那么这项工作的影响将是广泛的，因为它将（i）使世界各地的许多团体能够使用现有的基础设施采用快照3D光声成像技术，（ii）确定新的检测策略，以更低的成本扩展到数千个通道，（iii）使我的团队，合作者和其他人能够追求高分辨率超快多光谱3D成像用于生物医学应用。

The long-term objective of my research program is to develop snapshot 3D photoacoustic imaging for high-resolution, multispectral, ultrafast imaging of biochemical and biological processes in highly turbid media such as tissues of the human body. Snapshot 3D photoacoustic imaging has the potential to resolve differences between normal and diseased tissues (e.g. cancer) without a lengthy scanning procedure and sensitivity to motion artifacts. Snapshot 3D photoacoustic imaging represents a hybrid technology where a single pulse of laser light (5-10 ns) diffusely illuminates a medium. In response, optical absorbers (targets) in the medium generate acoustic waves at ultrasonic frequencies (0.2-10 MHz). Imaging results from detecting and recording, in parallel, the acoustic waves with a stationary array of ultrasonic transducers linked to data acquisition hardware. The photoacoustic recordings are then reconstructed into images representative of the location, size, shape, and optical properties of the targets. One of the main limitations of snapshot 3D photoacoustic imaging is poor image quality, especially for complex targets such as optical absorbers in biological tissue. Poor image quality is a result of practical channel density limitations due of currently available transducer array and data acquisition hardware. Even the best-equipped photoacoustic research groups have access to no more than 256 simultaneous detection channels. Therefore, groups have chosen to either scan the transducer array at the expense of the snapshot capability effectively to obtain the higher channel density needed to reconstruct high quality images. My group has chosen to develop stationary arrays for snapshot imaging by (i) optimizing transducer array designs for currently available channel densities to obtain images of comparable quality to much higher density systems, (ii) objectively evaluating the imaging performance of optimized designs, and (iii) developing new technologies that scale to several thousand channels practically and reliably. To achieve these three research objectives, the research plan will build upon methods developed by my group. First, we plan to design, optimize and test transducer arrays using cross-talk analysis. Cross-talk analysis provides an objective measure of the system sensitivity within the imaged volume (independent of image reconstruction method) and also provides estimates of the aliasing (overlap) of transducer signals from one location to another within the imaged volume. A transducer array design with high sensitivity and low aliasing throughout the image volume can be considered an optimal design. Second, we plan to apply conventional image quality assessment techniques to study imaging performance of the transducer array designs using signal fidelity and perceived visual quality metrics. Image quality metrics will be estimated for a series of imaging tasks that present targets of increasing geometric complexity to each optimized design. Last, we will examine conventional approach to extend existing data acquisition hardware to thousands of detection channels and investigate the sensitivity and bandwidth of a radically new optically-based acoustic transducer, which has potential to be fabricated into a large array with several thousand independent detection channels. If we are successful, then the impact of the work will be widespread as it will (i) enable many groups worldwide to adopt snapshot 3D photoacoustic imaging techniques using existing infrastructure, (ii) identify new detection strategies that scale to several thousand channels with lower cost, and (iii) enable my group, collaborators, and others to pursue high-resolution ultrafast multispectral 3D imaging for biomedical applications.