Automatic algorithm for skin profile detection in photoacoustic microscopy

4D spectral-spatial computational photoacoustic dermoscopy

Photoacoustic dermoscopy (PAD) is an emerging non-invasive imaging technology aids in the diagnosis of dermatological conditions by obtaining optical absorption information of skin tissues. Despite advances in PAD, it remains unclear how to obtain quantitative accuracy of the reconstructed PAD images according to the optical and acoustic properties of multilayered skin, the wavelength and distribution of excitation light, and the detection performance of ultrasound transducers. In this work, a computing method of four-dimensional (4D) spectral-spatial imaging for PAD is developed to enable quantitative analysis and optimization of structural and functional imaging of skin. This method takes the optical and acoustic properties of heterogeneous skin tissues into account, which can be used to correct the optical field of excitation light, detectable ultrasonic field, and provide accurate single-spectrum analysis or multi-spectral imaging solutions of PAD for multilayered skin tissues. A series of experiments were performed, and simulation datasets obtained from the computational model were used to train neural networks to further improve the imaging quality of the PAD system. All the results demonstrated the method could contribute to the development and optimization of clinical PADs by datasets with multiple variable parameters, and provide clinical predictability of photoacoustic (PA) data for human skin.

Automatic force-controlled 3D photoacoustic system for human peripheral vascular imaging

Photoacoustic (PA) imaging provides unique advantages in peripheral vascular imaging due to its high sensitivity to hemoglobin. Nevertheless, limitations associated with handheld or mechanical scanning by stepping motor techniques have precluded photoacoustic vascular imaging from advancing to clinical applications. As clinical applications require flexibility, affordability, and portability of imaging equipment, current photoacoustic imaging systems developed for clinical applications usually use dry coupling. However, it inevitably induces uncontrolled contact force between the probe and the skin. Through 2D and 3D experiments, this study proved that contact forces during the scanning could significantly affect the vascular shape, size, and contrast in PA images, due to the morphology and perfusion alterations of the peripheral blood vessels. However, there is no available PA system that can control forces accurately. This study presented an automatic force-controlled 3D PA imaging system based on a six-degree-of-freedom collaborative robot and a six-dimensional force sensor. It is the first PA system that achieves real-time automatic force monitoring and control. This paper's results, for the first time, demonstrated the ability of an automatic force-controlled system to acquire reliable 3D PA images of peripheral blood vessels. This study provides a powerful tool that will advance PA peripheral vascular imaging to clinical applications in the future.

A Signal Domain Object Segmentation Method for Ultrasound and Photoacoustic Computed Tomography

Image segmentation is important in improving the diagnostic capability of ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT), as it can be included in the image reconstruction process to improve image quality and quantification abilities. Segmenting the imaged object out of the background using image domain methods is easily complicated by low contrast, noise, and artifacts in the reconstructed image. Here, we introduce a new signal domain object segmentation method for USCT and PACT which does not require image reconstruction beforehand and is automatic, robust, computationally efficient, accurate, and straightforward. We first establish the relationship between the time-of-flight of the received first arrival waves and the object's boundary which is described by ellipse equations. Then, we show that the ellipses are tangent to the boundary. By looking for tangent points on the common tangent of neighboring ellipses, the boundary can be approximated with high fidelity. Imaging experiments of human fingers and mice cross-sections showed that our method provided equivalent or better segmentations than the optimal ones by active contours. In summary, our method greatly reduces the overall complexity of object segmentation and shows great potential in eliminating user dependency without sacrificing segmentation accuracy. The method can be further seamlessly incorporated into algorithms for other processing purposes in USCT and PACT, such as high-quality image reconstruction.

Three dimensional confocal photoacoustic dermoscopy with an autofocusing sono-opto probe

Photoacoustic dermoscopy (PAD) is uniquely positioned for the diagnosis and assessment of dermatological conditions because of its ability to visualize optical absorption contrast in vivo in three dimensions. In this Letter, we developed a 3D confocal PAD (3D-CPAD) equipped with an autofocusing sono-opto probe to facilitate the reconstruction of high-spatial-resolution imaging of skin with multilaminate structures in depth direction. The autofocusing sono-opto probe integrated a 10-mm electrowetting-based varifocal lens to automatically control the acoustic and optical confocal length, and an annular ultrasonic detector with a mid-frequency of ~32.8 MHz is coaxially configured for receiving photoacoustic signals. Using this sono-opto probe, the acoustic and optical confocal length-shifting range from ~7 to 43 mm with high image contrast and spatial resolution in the 3D image reconstruction. Autofocusing property tests and 3D human skin in vivo imaging were carried out to demonstrate the imaging capability of the 3D-CPAD for potential clinical foreground in noninvasive biopsies of skin disease.

Full-view in vivo skin and blood vessels profile segmentation in photoacoustic imaging based on deep learning

Photoacoustic (PA) microscopy allows imaging of the soft biological tissue based on optical absorption contrast and spatial ultrasound resolution. One of the major applications of PA imaging is its characterization of microvasculature. However, the strong PA signal from skin layer overshadowed the subcutaneous blood vessels leading to indirectly reconstruct the PA images in human study. Addressing the present situation, we examined a deep learning (DL) automatic algorithm to achieve high-resolution and high-contrast segmentation for widening PA imaging applications. In this research, we propose a DL model based on modified U-Net for extracting the relationship features between amplitudes of the generated PA signal from skin and underlying vessels. This study illustrates the broader potential of hybrid complex network as an automatic segmentation tool for the in vivo PA imaging. With DL-infused solution, our result outperforms the previous studies with achieved real-time semantic segmentation on large-size high-resolution PA images.

Dedicated photoacoustic imaging instrument for human periphery blood vessels: A new paradigm for understanding the vascular health

A novel photoacoustic imaging system based on a semi-ring transducer array is proposed to imageperipheralbloodvessels. The system's penetration depth is deep (~15 mm) with high spatial (~200 m) and temporal resolution. In a clinical study, volumetric photoacoustic data of limbs were obtained within the 50s (for a FOV of 15 cm4 cm) with the volunteers in the standing and sitting posture. Compared to the previous studies, our system has many advantages, including (1) Larger field of view; (2) Finer elevational and in-plane resolutions; (3) Enhanced 3D visualization of peripheralvascular networks; (4) Compact size and better portability. The 3D visualization and cross-sectional images of five healthy volunteers clearly show the vascular network and the system's ability to image submillimeter blood vessels. This high-resolution PA system has great potential for imaging human periphery vasculatures noninvasively in clinical research.

3D PHOVIS: 3D photoacoustic visualization studio

Photoacoustic (PA) imaging (or optoacoustic imaging) is a novel biomedical imaging method in biological and medical research. This modality performs morphological, functional, and molecular imaging with and without labels in both microscopic and deep tissue imaging domains. A variety of innovations have enhanced 3D PA imaging performance and thus has opened new opportunities in preclinical and clinical imaging. However, the 3D visualization tools for PA images remains a challenge. There are several commercially available software packages to visualize the generated 3D PA images. They are generally expensive, and their features are not optimized for 3D visualization of PA images. Here, we demonstrate a specialized 3D visualization software package, namely 3D Photoacoustic Visualization Studio (3D PHOVIS), specifically targeting photoacoustic data, image, and visualization processes. To support the research environment for visualization and fast processing, we incorporated 3D PHOVIS onto the MATLAB with graphical user interface and developed multi-core graphics processing unit modules for fast processing. The 3D PHOVIS includes following modules: (1) a mosaic volume generator, (2) a scan converter for optical scanning photoacoustic microscopy, (3) a skin profile estimator and depth encoder, (4) a multiplanar viewer with a navigation map, and (5) a volume renderer with a movie maker. This paper discusses the algorithms present in the software package and demonstrates their functions. In addition, the applicability of this software to ultrasound imaging and optical coherence tomography is also investigated. User manuals and application files for 3D PHOVIS are available for free on the website (www.boa-lab.com). Core functions of 3D PHOVIS are developed as a result of a summer class at POSTECH, "High-Performance Algorithm in CPU/GPU/DSP, and Computer Architecture." We believe our 3D PHOVIS provides a unique tool to PA imaging researchers, expedites its growth, and attracts broad interests in a wide range of studies.

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.

Skin Surface Detection in 3D Optoacoustic Mesoscopy Based on Dynamic Programming

Optoacoustic (photoacoustic) mesoscopy offers unique capabilities in skin imaging and resolves skin features associated with detection, diagnosis, and management of disease. A critical first step in the quantitative analysis of clinical optoacoustic images is to identify the skin surface in a rapid, reliable, and automated manner. Nevertheless, most common edge- and surface-detection algorithms cannot reliably detect the skin surface on 3D raster-scan optoacoustic mesoscopy (RSOM) images, due to discontinuities and diffuse interfaces in the image. We present herein a novel dynamic programming approach that extracts the skin boundary as a 2D surface in one single step, as opposed to consecutive extraction of several independent 1D contours. A domain-specific energy function is introduced, taking into account the properties of volumetric optoacoustic mesoscopy images. The accuracy of the proposed method is validated on scans of the volar forearm of 19 volunteers with different skin complexions, for which the skin surface has been traced manually to provide a reference. In addition, the robustness and the limitations of the method are demonstrated on data where the skin boundaries are low-contrast or ill-defined. The automatic skin surface detection method can improve the speed and accuracy in the analysis of quantitative features seen on the RSOM images and accelerate the clinical translation of the technique. Our method can likely be extended to identify other types of surfaces in the RSOM and other imaging modalities.

Super-resolution localization photoacoustic microscopy using intrinsic red blood cells as contrast absorbers

Photoacoustic microscopy (PAM) has become a premier microscopy tool that can provide the anatomical, functional, and molecular information of animals and humans in vivo. However, conventional PAM systems suffer from limited temporal and/or spatial resolution. Here, we present a fast PAM system and an agent-free localization method based on a stable and commercial galvanometer scanner with a custom-made scanning mirror (L-PAM-GS). This novel hardware implementation enhances the temporal resolution significantly while maintaining a high signal-to-noise ratio (SNR). These improvements allow us to photoacoustically and noninvasively observe the microvasculatures of small animals and humans in vivo. Furthermore, the functional hemodynamics, namely, the blood flow rate in the microvasculature, is successfully monitored and quantified in vivo. More importantly, thanks to the high SNR and fast B-mode rate (500 Hz), by localizing photoacoustic signals from captured red blood cells without any contrast agent, unresolved microvessels are clearly distinguished, and the spatial resolution is improved by a factor of 2.5 in vivo. L-PAM-GS has great potential in various fields, such as neurology, oncology, and pathology.

Segmentation of vessel structures from photoacoustic images with reliability assessment

Photoacoustic imaging enables the imaging of soft biological tissue with combined optical contrast and ultrasound resolution. One of the targets of interest is tissue vasculature. However, the photoacoustic images may not directly provide the information on, for example, vasculature structure. Therefore, the images are improved by reducing noise and artefacts, and processed for better visualisation of the target of interest. In this work, we present a new segmentation method of photoacoustic images that also straightforwardly produces assessments of its reliability. The segmentation depends on parameters which have a natural tendency to increase the reliability as the parameter values monotonically change. The reliability is assessed by counting classifications of image voxels with different parameter values. The resulting segmentation with reliability offers new ways and tools to analyse photoacoustic images and new possibilities for utilising them as anatomical priors in further computations. Our MATLAB implementation of the method is available as an open-source software package [P. Raumonen, Matlab, 2018].

Delay-multiply-and-sum-based synthetic aperture focusing in photoacoustic microscopy

We propose an improved version of a synthetic aperture focusing technique (SAFT) based on a delay-multiply-and-sum algorithm for acoustic-resolution photoacoustic microscopy (AR-PAM). In this method, the photoacoustic (PA) signals from multiple scan-lines are combinatorially coupled, multiplied, and then summed. This process can be considered a correlation operation of the PA signals in each scan-line, so the spatial coherent information between the PA signals can be efficiently extracted. By applying this method in conventional AR-PAM, lateral resolution and signal-to-noise ratio in out-of-focus regions are much improved compared with those estimated from the previously developed SAFT, respectively, thereby achieving the extension of the imaging focal region. Our phantom and in vivo imaging experiments prove the validity of our proposed method.

In vivo corneal neovascularization imaging by optical-resolution photoacoustic microscopy

Corneal neovascularization leads to blurred vision, thus in vivo visualization is essential for pathological studies in animal models. Photoacoustic (PA) imaging can delineate microvasculature and hemodynamics noninvasively, which is suitable for investigating corneal neovascularization. In this study, we demonstrate in vivo imaging of corneal neovascularization in the mouse eye by optical-resolution photoacoustic microscopy (OR-PAM), where corneal neovascularization is induced by deliberate alkali burn injuries in C57BL6/J inbred mice corneas on the left eye. We used OR-PAM to image five mice with corneal alkali burn injuries; the uninjured eyes (right eye) in these mice are then used as the controls. Corneal images acquired by OR-PAM with and without alkali burn injury are compared, clear signs of corneal neovascularization are present in the OR-PAM images of injured eyes; the OR-PAM results are also confirmed by postmortem fluorescence-labeled confocal microscopy.

Imaging of an inflammatory injury in the newborn rat brain with photoacoustic tomography

Background

The precise assessment of cerebral saturation changes during an inflammatory injury in the developing brain, such as seen in periventricular leukomalacia, is not well defined. This study investigated the impact of inflammation on locoregional cerebral oxygen saturation in a newborn rodent model using photoacoustic imaging.

Methods

1 mg/kg of lipopolysaccharide(LPS) diluted in saline or saline alone was injected under ultrasound guidance directly in the corpus callosum of P3 rat pups. Coronal photoacoustic images were carried out 24 h after LPS exposure. Locoregional oxygen saturation (SO₂) and resting state connectivity were assessed in the cortex and the corpus callosum. Microvasculature was then evaluated on cryosection slices by lectin histochemistry.

Results

Significant reduction of SO₂ was found in the corpus callosum; reduced SO₂ was also found in the cortex ipsilateral to the injection site. Seed-based functional connectivity analysis showed that bilateral connectivity was not affected by LPS exposure. Changes in locoregional oxygen saturation were accompanied by a significant reduction in the average length of microvessels in the left cortex but no differences were observed in the corpus callosum.

Conclusion

Inflammation in the developing brain induces marked reduction of locoregional oxygen saturation, predominantly in the white matter not explained by microvascular degeneration. The ability to examine regional saturation offers a new way to monitor injury and understand physiological disturbance non-invasively.

Photoacoustic Microscopy in Tissue Engineering

Photoacoustic tomography (PAT) is an attractive modality for noninvasive, volumetric imaging of scattering media such as biological tissues. By choosing the ultrasonic detection frequency, PAT enables scalable spatial resolution with desired imaging depth up to ~7 cm while maintaining a high depth-to-resolution ratio of ~200 and consistent optical absorption contrasts. Photoacoustic microscopy (PAM), the microscopic embodiment of PAT, aims to image at millimeter depth and micrometer-scale resolution. PAM is well-suited for characterizing three-dimensional scaffold-based samples, including scaffolds themselves, cells, and blood vessels, both qualitatively and quantitatively. Here we review our previous work on applications of PAM in tissue engineering and then discuss its future developments.

Investigation of neovascularization in three-dimensional porous scaffolds in vivo by a combination of multiscale photoacoustic microscopy and optical coherence tomography

It is a grand challenge to visualize and assess in vivo neovascularization in a three-dimensional (3D) scaffold noninvasively, together with high spatial resolution and deep penetration depth. Here we used multiscale photoacoustic microscopy (PAM), including acoustic-resolution PAM (AR-PAM) and optical-resolution PAM (OR-PAM), to chronically monitor neovascularization in an inverse opal scaffold implanted in a mouse model up to 6 weeks by taking advantage of the optical absorption contrast intrinsic to hemoglobin molecules in red blood cells. By combining with optical coherence tomography (OCT) based on optical scattering contrast, we also demonstrated the capability to simultaneously image and analyze the vasculature and the scaffold in the same mouse. The hybrid system containing OR-PAM and OCT offered a fine lateral resolution of ∼5 μm and a penetration depth of ∼1 mm into the scaffold/tissue construct. AR-PAM further extended the penetration depth up to ∼3 mm at a lateral resolution of ∼45 μm. By quantifying the 3D PAM data, we further examined the effect of pore size (200 vs. 80 μm) of a scaffold on neovascularization. The data collected from PAM were consistent with those obtained from traditional invasive, labor-intensive histologic analyses.

Adaptive synthetic-aperture focusing technique for microvasculature imaging using photoacoustic microscopy

To improve the lateral resolution of the blood vessels along arbitrary direction out of focus in photoacoustic microscopy (PAM), we propose an adaptive synthetic-aperture focusing technique (ASAFT) for microvasculature imaging which can be automatically applied to each branch of blood vessels, based on our previous two-dimensional (2D) SAFT. The ASAFT is validated both in the phantom study and in vivo imaging. The results demonstrate that ASAFT can provide images of blood vessels with better lateral resolution both at different depths and along various directions compared with one-dimensional and 2D SAFT.

Photoacoustic tomography: fundamentals, advances and prospects

Optical microscopy has been contributing to the development of life science for more than three centuries. However, due to strong optical scattering in tissue, its in vivo imaging ability has been restricted to studies at superficial depths. Advances in photoacoustic tomography (PAT) now allow multiscale imaging at depths from sub-millimeter to several centimeters, with spatial resolutions from sub-micrometer to sub-millimeter. Because of this high scalability and its unique optical absorption contrast, PAT is capable of performing anatomical, functional, molecular and fluid-dynamic imaging at various system levels, and is playing an increasingly important role in fundamental biological research and clinical practice. This review discusses recent technical progress in PAT and presents corresponding applications. It ends with a discussion of several prospects and their technical challenges.

Photoacoustic ophthalmoscopy for in vivo retinal imaging

We have developed a non-invasive photoacoustic ophthalmoscopy (PAOM) for in vivo retinal imaging. PAOM detects the photoacoustic signal induced by pulsed laser light shined onto the retina. By using a stationary ultrasonic transducer in contact with the eyelids and scanning only the laser light across the retina, PAOM provides volumetric imaging of the retinal micro-vasculature and retinal pigment epithelium at a high speed. For B-scan frames containing 256 A-lines, the current PAOM has a frame rate of 93 Hz, which is comparable with state-of-the-art commercial spectral-domain optical coherence tomography (SD-OCT). By integrating PAOM with SD-OCT, we further achieved OCT-guided PAOM, which can provide multi-modal retinal imaging simultaneously. The capabilities of this novel technology were demonstrated by imaging both the microanatomy and microvasculature of the rat retina in vivo.

Photoacoustic imaging and characterization of the microvasculature

Photoacoustic (optoacoustic) tomography, combining optical absorption contrast and highly scalable spatial resolution (from micrometer optical resolution to millimeter acoustic resolution), has broken through the fundamental penetration limit of optical ballistic imaging modalities-including confocal microscopy, two-photon microscopy, and optical coherence tomography-and has achieved high spatial resolution at depths down to the diffusive regime. Optical absorption contrast is highly desirable for microvascular imaging and characterization because of the presence of endogenous strongly light-absorbing hemoglobin. We focus on the current state of microvascular imaging and characterization based on photoacoustics. We first review the three major embodiments of photoacoustic tomography: microscopy, computed tomography, and endoscopy. We then discuss the methods used to characterize important functional parameters, such as total hemoglobin concentration, hemoglobin oxygen saturation, and blood flow. Next, we highlight a few representative applications in microvascular-related physiological and pathophysiological research, including hemodynamic monitoring, chronic imaging, tumor-vascular interaction, and neurovascular coupling. Finally, several potential technical advances toward clinical applications are suggested, and a few technical challenges in contrast enhancement and fluence compensation are summarized.