Realtime high resolution 3D multispectral photoacoustic imaging

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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.