Acoustic Resolution Photoacoustic Microscopy System Research Articles

Depth-extended acoustic-resolution photoacoustic microscopy based on a two-stage deep learning network.

Acoustic resolution photoacoustic microscopy (AR-PAM) is a major modality of photoacoustic imaging. It can non-invasively provide high-resolution morphological and functional information about biological tissues. However, the image quality of AR-PAM degrades rapidly when the targets move far away from the focus. Although some works have been conducted to extend the high-resolution imaging depth of AR-PAM, most of them have a small focal point requirement, which is generally not satisfied in a regular AR-PAM system. Therefore, we propose a two-stage deep learning (DL) reconstruction strategy for AR-PAM to recover high-resolution photoacoustic images at different out-of-focus depths adaptively. The residual U-Net with attention gate was developed to implement the image reconstruction. We carried out phantom and in vivo experiments to optimize the proposed DL network and verify the performance of the proposed reconstruction method. Experimental results demonstrated that our approach extends the depth-of-focus of AR-PAM from 1mm to 3mm under the 4 mJ/cm2 light energy used in the imaging system. In addition, the imaging resolution of the region 2 mm far away from the focus can be improved, similar to the in-focus area. The proposed method effectively improves the imaging ability of AR-PAM and thus could be used in various biomedical studies needing deeper depth.

Super Wide-Field Photoacoustic Microscopy of Animals and Humans In Vivo

Acoustic-resolution photoacoustic micro-scopy (AR-PAM) is an emerging biomedical imaging modality that combines superior optical sensitivity and fine ultrasonic resolution in an optical quasi-diffusive regime (~1-3 mm in tissues). AR-PAM has been explored for anatomical, functional, and molecular information in biological tissues. Heretofore, AR-PAM systems have suffered from a limited field-of-view (FOV) and/or slow imaging speed, which have precluded them from routine preclinical and clinical applications. Here, we demonstrate an advanced AR-PAM system that overcomes both limitations of previous AR-PAM systems. The new AR-PAM system demonstrates a super wide-field scanning that utilized a 1-axis water-proofing microelectromechanical systems (MEMS) scanner integrated with two linear stepper motor stages. We achieved an extended FOV of 36 ×80 mm2 by mosaicking multiple volumetric images of 36 ×2.5 mm2 with a total acquisition time of 224 seconds. For one volumetric data (i.e., 36 ×2.5 mm2), the B-scan imaging speed over the short axis (i.e., 2.5 mm) was 83 Hz in humans. The 3D volumetric image was also provided by using MEMS mirror scanning along the X-axis and stepper-motor scanning along the Y-axis. The super-wide FOV mosaic image was realized by registering and merging all individual volumetric images. Finally, we obtained multi-plane whole-body in-vivo PA images of small animals, illustrating distinct multi-layered structures including microvascular networks and internal organs. Importantly, we also visualized microvascular networks in human fingers, palm, and forearm successfully. This advanced MEMS-AR-PAM system could potentially enable hitherto not possible wide preclinical and clinical applications.

A versatile dark-field acoustic-resolution photoacoustic microscopy system aided by 3D printing.

Since the dark-field acoustic-resolution photoacoustic microscopy (AR-PAM) was invented over one decade ago, its powerful imaging capability made this system successful. In this work, we designed and tested an AR-PAM system whose key parts are relied on 3D printing and fiber bundles. This new design not only makes it much simpler to develop a robust PAM system, but also the illumination angle is adjustable to aid for different applications. Our simulation study and phantom experiments demonstrated that this design has the comparable performance with traditional dark-field AR-PAM.

Feasibility of co-registered ultrasound and acoustic-resolution photoacoustic imaging of human colorectal cancer.

Colorectal cancer is the second leading cause of cancer death in the United States. Significant limitations in screening and surveillance modalities continue to hamper early detection of primary cancers or recurrences after therapy. In this study, we describe a new registered ultrasound (US) and acoustic-resolution photoacoustic microscopy (AR-PAM) system and report its initial testing in ex vivo human colorectal tissue. A total of 8 colorectal specimens were imaged, which included 2 polyps, 4 malignant colon cancers, and 2 treated colorectal cancers. In each specimen, normal tissue was also imaged for internal control. Initial data have demonstrated the feasibility of identifying colorectal cancer imaging features and the invasion depth using co-registered US and an AR-PAM system. In normal tissue, we found that our system consistently demonstrates the multi-layer structure of normal colonic tissue while differentiating layers with elevated vascularity; these findings highly correlated with histologic findings of each specimen. For malignant colorectal samples, the tissue structure is highly disorganized as seen in US, and photoacoustic imaging revealed distorted vascular distribution inside the tumor. Notably, AR-PAM of tumor beds after complete tumor destruction by radiation and chemotherapy yielded a pattern identical to benign tissue. Quantitative analysis of photoacoustic spectral slope has demonstrated more high-frequency components in malignant tissue as compared to the normal colon tissue, which may be caused by significantly increased microvessel networks. In summary, we demonstrate the successful differentiation of benign and malignant colorectal tissue with our co-registered ultrasound and photoacoustic system.

Dual-view acoustic-resolution photoacoustic microscopy with enhanced resolution isotropy.

Acoustic-resolution photoacoustic microscopy (AR-PAM) can provide penetration depths beyond the optical diffusion limit, but its lateral resolution is typically much worse than its axial resolution, resulting in a low-resolution isotropy. We herein present a dual-view AR-PAM (DV-AR-PAM) system that exploits two orthogonally arranged focused ultrasonic transducers. Taking advantage of their complementary acoustic detecting profiles, DV-AR-PAM allows the fusion of the dual-view signals, resulting in an enhancement in the resolution isotropy from 29% to 95% within one imaging plane, as demonstrated by simulation results on densely packed particles and experimental results on a single carbon fiber. The application of this method in vivo revealed distinct microvasculature structures in mouse skin that were previously indistinguishable with single-view detection, demonstrating the potential of DV-AR-PAM for vascular and neurological studies.

Focal zone integral and multiple axial scanning based acoustic resolution photoacoustic microscopy with high lateral resolution in-depth

Acoustic resolution photoacoustic microscopy (ARPAM) combines the advantages of high optical contrast, and high ultrasonic spatial resolution and penetration. However, in photoacoustic microscopy (PAM), the information from deep regions can be greatly affected by the shallow targets, and most importantly, the irreconcilable conflict between the lateral resolution and depth of fields has always be a major factor that limits the imaging quality. In this work, an ARPAM system was developed, in which a non-coaxial arrangement of light illumination and acoustic detection was adopted to alleviate the influence of the tissue surface on the deep targets, and a novel focal zone integral algorithm was applied with multiple axial scanning to improve the lateral resolution. Phantom experiment results show that, the build system can maintain a consistent high lateral resolution of 0.6 mm over a large range in axial direction, which is close to the theoretical calculations. The following tumor imaging results on nude mice indicate that, the proposed method can provide more in-depth information compared with the conventional back detection ARPAM method. With the development of fast repetition lasers and image scanning technologies, the proposed method may play an important role in cerebral vascular imaging, cervical cancer photoacoustic endoscopic detection, and superficial tumor imaging.