Photoacoustic Microscopy Imaging Research Articles

Unveiling placental development in circadian rhythm-disrupted mice: A photo-acoustic imaging study on unstained tissue

IntroductionCircadian rhythm disruption has garnered significant attention for its adverse effects on human health, particularly in reproductive medicine and fetal well-being. Assessing pregnancy health often relies on diagnostic markers such as the labyrinth zone (LZ) proportion within the placenta. This study aimed to investigate the impact of disrupted circadian rhythms on placental health and fetal development using animal models. Methods and resultsEmploying unstained photo-acoustic microscopy (PAM) and hematoxylin and eosin (HE)-stained images, we found them mutually reinforcing. Our images revealed the role of maternal circadian rhythm disrupted group (MCRD) on the LZ and fetus weight: a decrease in LZ area from 5.01 (4.25) mm2 HE (PAM) to 3.58 (2.62) mm2 HE (PAM) on day 16 and 6.48 (5.16) mm2 HE (PAM) to 4.61 (3.03) mm2 HE (PAM) on day 18, resulting in 0.71 times lower fetus weights. We have discriminated a decrease in the mean LZ to placenta area ratio from 64 % to 47 % on day 18 in mice with disrupted circadian rhythms with PAM. DiscussionThe study highlights the negative influence of circadian rhythm disruption on placental development and fetal well-being. Reduced LZ area and fetal weights in the MCRD group suggest compromised placental function under disrupted circadian rhythms. PAM imaging proved to be an efficient technique for assessing placental development, offering advantages over traditional staining methods. These findings contribute to understanding the underlying mechanisms of circadian disruption on reproductive health and fetal development. Further research is needed to explore interventions to mitigate these effects and improve pregnancy outcomes.

Engineering optimal gold nanorod-loaded hollow mesoporous organosilica nanotheranostics for NIR-II photoacoustic microscopy imaging and tumor synergistic therapy

Biodegradable hollow mesoporous organosilica nanoparticles (HMON)-based nanotheranostics has recently gained growing interests due to their tremendous potential as an attractive platform for cancer imaging and therapy. However, the engineering of HMON-based nanotheranostics for size-dependent biological profile on in vivo tumor uptake, biodistribution and retention in tumor region have not been achieved to date. Here, a novel tumor microenvironment (TME)-activated nanoplatform employing miniature gold nanorod-loaded HMON (Au@HMON) with tunable hollow cavity of HMON coating is presented, and its application in the second near infrared (NIR-II, 1000–1700 nm) window photoacoustic microscopy (PAM) imaging-guided synergistic chemo-photothermal therapy is studied by loading doxorubicin (DOX). The cancer cell membrane (CCM) biomimetic nanotheranostics (Au@HMON-DOX@CCM) exhibited a high photothermal conversion efficiency of 41.1 % for photothermal therapy (PTT) and PAM imaging. Among the three investigated nanotheranostics, the 221 nm-nanotheranostics exhibited stronger PAM signal and higher drug loading efficacy than the small counterparts (156- and 186-nm) due to the thicker HMON coating layer, larger surface area and intermediate void structure. Therefore, synergistic chemo-photothermal therapy using 221 nm-nanotheranostics is achieved to efficiently inhibit tumor growth. This strategy affords design parameters for engineering HMON-based “all-in-one” nanotheranostics for photoacoustic imaging-guided cancer treatment.

The deterioration of microstructure and biochemical components in cancellous bone characterizing by the photoacoustic microscopy imaging

Abstract Background/Objective: Osteoporosis is mainly characterized by a deterioration of microstructure and a loss of biochemical components in bone tissues. Developing an imaging technique for measuring bone tissue microstructure and the biochemical components is of great significance for the early diagnosis of osteoporosis. Photoacoustic microscopy (PAM) has the advantage of high optical resolution and the potential to diagnose osteoporosis. In this study, we investigated the feasibility of the photoacoustic microscopy (PAM) technique for bone tissue imaging, and the deterioration of microstructure and biochemical components in cancellous bone was characterized by the PAM. Statement of Contribution/Methods: We performed the optical-resolution photoacoustic microscopy (OR-PAM) for bone tissue imaging and the trabecular microstructure and hydroxyapatite (HAP) were degraded by immersion in JYBL-I solution. The PAM imaging method was developed for the measurement of the surface and subsurface of cancellous bone with a high resolution. Specifically, a 532 nm pulse laser was used to excite the PA signal from the bone. The PA signal sampling frequency was 80 MHz. A motor rotated a 15 MHz central frequency transducer to receive 1000 × 1000 × 250 points data. The envelope of the signal was obtained using the Hilbert transform for reconstruction. Then, the JYBL-I solution was used to reduce the HAP component in the bone. The PAM imaging was performed after different immersion times, (i.e., at 0, 5, and 10 mins). In the PAM measurement of the cancellous bone, the imaging area was a cylinder with an 8 mm diameter and an 8 μm/pixel resolution. Results/Discussion: The results showed that the trabecular microstructure could be imaged with a relatively high quality using the PAM technique. With the different extent of HAP degradation by immersion in JYBL-I solution, some trabecular bone disappeared corresponding with PA signals decreased significantly in amplitude. Conclusion: These results indicate that the PA technique has potential application in the characterization of bone microstructure and biochemical components with a high resolution.

Feasibility of Prostatitis Evaluation Based on Photoacoustic Microscopy

Abstract This study aims to investigate the feasibility of using photoacoustic microscopy for the diagnosis of prostatitis. We induced inflammation in rats to establish a model of prostatitis using Freund’s Complete Adjuvant (FCA). Prostate tissues from both the model and control groups were extracted and processed into histological sections. We explored the photoacoustic microscopy imaging results of unstained sections, consistent with the histological detection results using HE staining. Inflammation was found to enhance the photoacoustic signals. Subsequently, we conducted photoacoustic microscopy imaging on all samples, and the detection results were nearly consistent with the diagnoses made by medical professionals. Finally, we quantified the collected photoacoustic signals to classify the severity of prostatitis.

Research on 3D Reconstruction of Paleontological Fossils Based on Photoacoustic Microscopy

Abstract The focus on three-dimensional morphological analysis of endogenous trace fossils has emerged as a prominent aspect in the study of palaeobiological fossils. Photoacoustic imaging technology, renowned for its deep penetration, high resolution and non-destructiveness, holds considerable promise in exploring fossil morphology. In this work, a solid-coupling-based photoacoustic microscopic imaging system was developed, leveraging this technology to investigate small-scale physical fossils. The proposed system enabled layered imaging of various fossil specimens, achieving a lateral resolution exceeds 35 μm and an axial resolution superior to 8.8815 μm. The three-dimensional reconstruction results were obtained through image processing algorithms. This system was proved to be efficient to imaging the small-scale physical fossils.

3D computational modeling of multispectral photoacoustic microscopy: Simulations aiding systematic optimization and data acquisition

Abstract Photoacoustic microscopy (PAM), a fruitful application modality for photoacoustic imaging, is capable of directly measuring optical absorption properties in skin tissue, providing high-contrast, high-resolution medical images as well as functional and pathologic information. However, optical attenuation and unknown optical and acoustic nonuniformities limit its imaging performance in deep tissue regions. New instrumentation, image reconstruction, and artificial intelligence methods are being investigated to overcome these limitations, and a reliable PAM simulation tool is required for the effective implementation of these methods. In this paper, we propose and validate a 3D quantitative computational multispectral PAM imaging model. It provides a theoretical basis for the application of quantitative PAM in skin diagnosis and aids in the development and optimization of PAM devices, as well as the acquisition of deep learning datasets.

Selective nanosecond laser removal of retinal pigment epithelium for cell therapy

Retinal pigment epithelial (RPE) cells play a crucial role in the health of the retina, and their dysfunction is associated with various ocular diseases. The transplantation of RPE cells has been proposed as a potential treatment for numerous degenerative diseases, including geographic atrophy from macular degeneration. However, current models to induce RPE damage in animal models prior to transplantation involve mechanical scraping, chemical administration, or laser photocoagulation techniques, which can damage the overlying neurosensory retina. This study aims to investigate the feasibility and efficacy of nanosecond duration laser treatment to safely remove large areas of RPE cells without causing damage to the adjacent tissue or affecting the retinal architecture. Twelve pigmented rabbits were treated with a nanosecond laser on each eye at a laser energy ranging from 200 to 800 nJ with a treated area of 5 × 5 mm2. Human induced pluripotent stem cells-differentiated to RPE (hiPSC-RPE) cells labeled with indocyanine green (ICG), an FDA approved dye, were transplanted subretinally into the damaged RPE areas at day 14 post-laser treatment. The RPE atrophy and hiPSC-RPE cell survival was evaluated and monitored over a period of 14 days using color photography, fluorescein angiography (FA), photoacoustic microscopy (PAM), and optical coherence tomography (OCT) imaging. All treated eyes demonstrated focal RPE loss with a success rate of 100%. The injured RPE layers and the transplanted hiPSC-RPE cells were visualized in three dimensions using PAM and OCT. By performing PAM at an optical wavelength of 700 nm, the location of hiPSC-RPE cells were identified and distinguished from the surrounding RPE cells, and the induced PA signal increased up to 18 times. Immunohistochemistry results confirmed the grafted hiPSC-RPE replaced regions of RPE damage. This novel technique has the potential to serve as an animal model of RPE degeneration, to improve models of RPE transplantation, and may help accelerate translation of this therapeutic strategy for clinical use.

Accelerating photoacoustic microscopy by reconstructing undersampled images using diffusion models

Photoacoustic Microscopy (PAM) integrates optical and acoustic imaging, offering enhanced penetration depth for detecting optical-absorbing components in tissues. Nonetheless, challenges arise in scanning large areas with high spatial resolution. With speed limitations imposed by laser pulse repetition rates, the potential role of computational methods is highlighted in accelerating PAM imaging. We propose a novel and highly adaptable algorithm named DiffPam that utilizes diffusion models to speed up the photoacoustic imaging process. We leveraged a diffusion model trained exclusively on natural images, comparing its performance with an in-domain trained U-Net model using a dataset focused on PAM images of mice brain microvasculature. Our findings indicate that DiffPam performs similarly to a dedicated U-Net model without needing a large dataset. We demonstrate that scanning can be accelerated fivefold with limited information loss. We achieved a 24.70%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$24.70\\%$$\\end{document} increase in peak signal-to-noise ratio and a 27.54%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$27.54\\%$$\\end{document} increase in structural similarity index compared to the baseline bilinear interpolation method. The study also introduces the efficacy of shortened diffusion processes for reducing computing time without compromising accuracy. DiffPam stands out from existing methods as it does not require supervised training or detailed parameter optimization typically needed for other unsupervised methods. This study underscores the significance of DiffPam as a practical algorithm for reconstructing undersampled PAM images, particularly for researchers with limited artificial intelligence expertise and computational resources.

Reconstructing Cancellous Bone From Down-Sampled Optical-Resolution Photoacoustic Microscopy Images With Deep Learning

ObjectiveBone diseases deteriorate the microstructure of bone tissue. Optical-resolution photoacoustic microscopy (OR-PAM) enables high spatial resolution of imaging bone tissues. However, the spatiotemporal trade-off limits the application of OR-PAM. The purpose of this study was to improve the quality of OR-PAM images without sacrificing temporal resolution. MethodsIn this study, we proposed the Photoacoustic Dense Attention U-Net (PADA U-Net) model, which was used for reconstructing full-scanning images from under-sampled images. Thereby, this approach breaks the trade-off between imaging speed and spatial resolution. ResultsThe proposed method was validated on resolution test targets and bovine cancellous bone samples to demonstrate the capability of PADA U-Net in recovering full-scanning images from under-sampled OR-PAM images. With a down-sampling ratio of [4, 1], compared to bilinear interpolation, the Peak Signal-to-Noise Ratio and Structural Similarity Index Measure values (averaged over the test set of bovine cancellous bone) of the PADA U-Net were improved by 2.325 dB and 0.117, respectively. ConclusionThe results demonstrate that the PADA U-Net model reconstructed the OR-PAM images well with different levels of sparsity. Our proposed method can further facilitate early diagnosis and treatment of bone diseases using OR-PAM.

Contrast-enhanced near-infrared photoacoustic microscopy and optical coherence tomography imaging of rat fundus

Abstract In this paper, we design a multimodal visible/near-infrared photoacoustic microscopy and optical coherence tomography (VIS/NIR-PAM-OCT) system for imaging both retina and retinal pigment epithelium (RPE)/choroid complex layer. F127 and DSPE-PEG-cRGD encapsulated IR-1048 nanoparticles (FINPs) exhibiting absorption peak up to 1,064 nm were utilized as contrast agents to enhance NIR-PAM for in vivo imaging of fundus tissues. The fundus structure and vessels are clearly visualized by the multimodal imaging, and their parameters were quantitatively analyzed. NIR-PAM and OCT imaging of fundus were time-serially monitored over 60 min following the intravenous injection of FINPs into rats. The results indicated a 134 % increase in image signals in PAM at 1 min, along with an 8.23 % intensity enhancement in OCT. Moreover, laser-induced choroidal neovascularization (CNV) was specifically detected and accurately quantified using VIS/NIR-PAM-OCT. Lastly, FINPs demonstrated excellent biocompatibility in hematology analysis and pathology testing.

UPAMNet: A unified network with deep knowledge priors for photoacoustic microscopy

Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. With the development of deep learning techniques, convolutional neural networks have been used for PAM image resolution enhancement and denoising. However, there exist several inherent challenges for this approach. This work presents a Unified PhotoAcoustic Microscopy image reconstruction Network (UPAMNet) for both PAM image super-resolution and denoising. The proposed method takes advantage of deep image priors by incorporating three effective attention-based modules and a mixed training constraint at both pixel and perception levels. The generalization ability of the model is evaluated in details and experimental results on different PAM datasets demonstrate the superior performance of the method. Experimental results show improvements of 0.59 dB and 1.37 dB, respectively, for 1/4 and 1/16 sparse image reconstruction, and 3.9 dB for image denoising in peak signal-to-noise ratio.

Efficient Assessment of Tumor Vascular Shutdown by Photodynamic Therapy on Orthotopic Pancreatic Cancer Using High-Speed Wide-Field Waterproof Galvanometer Scanner Photoacoustic Microscopy.

To identify the vascular alteration by photodynamic therapy (PDT), the utilization of high-resolution, high-speed, and wide-field photoacoustic microscopy (PAM) has gained enormous interest. The rapid changes in vasculature during PDT treatment and monitoring of tumor tissue activation in the orthotopic pancreatic cancer model have received limited attention in previous studies. Here, a fully two-axes waterproof galvanometer scanner-based photoacoustic microscopy (WGS-PAM) system was developed for in vivo monitoring of dynamic variations in micro blood vessels due to PDT in an orthotopic pancreatic cancer mouse model. The photosensitizer (PS), Chlorin e6 (Ce6), was utilized to activate antitumor reactions in response to the irradiation of a 660 nm light source. Microvasculatures of angiogenesis tissue were visualized on a 40 mm2 area using the WGS-PAM system at 30 min intervals for 3 h after the PDT treatment. The decline in vascular intensity was observed at 24.5% along with a 32.4% reduction of the vascular density at 3 h post-PDT by the analysis of PAM images. The anti-vascularization effect was also identified with fluorescent imaging. Moreover, Ce6-PDT increased apoptotic and necrotic markers while decreasing vascular endothelial growth factor (VEGF) expression in MIA PaCa-2 and BxPC-3 pancreatic cancer cell lines. The approach of the WGS-PAM system shows the potential to investigate PDT effects on the mechanism of angiographic dynamics with high-resolution wide-field imaging modalities.

Longitudinal Monitoring of Angiogenesis in a Murine Window Chamber Model In Vivo.

Angiogenesis induced by growth factor administration, which can augment the blood supply in regenerative applications, has drawn wide attention in medical research. Longitudinal monitoring of vascular structure and development in vivo is important for understanding and evaluating the dynamics of involved biological processes. In this work, a dual-modality imaging system consisting of photoacoustic microscopy (PAM) and optical coherence tomography (OCT) was applied for noninvasive in vivo imaging of angiogenesis in a murine model. Fibrin scaffolds, with and without basic fibroblast growth factor (bFGF), were implanted in a flexible imaging window and longitudinally observed over 9 days. Imaging was conducted at 3, 5, 7, and 9 days after implantation to monitor vascularization in and around the scaffold. Several morphometric parameters were derived from the PAM images, including vessel area density (VAD), total vessel length (TVL), and vessel mean diameter (VMD). On days 7 and 9, mice receiving bFGF-laden fibrin gels exhibited significantly larger VAD and TVL compared to mice with fibrin-only gels. In addition, VMD significantly decreased in +bFGF mice versus fibrin-only mice on days 7 and 9. Blood vessel density, evaluated using immunohistochemical staining of explanted gels and underlying tissue on day 9, corroborated the findings from the PAM images. Overall, the experimental results highlight the utility of a dual-modality imaging system in longitudinally monitoring of vasculature in vivo with high resolution and sensitivity, thereby providing an effective tool to study angiogenesis.

Advanced nanomaterials for imaging of eye diseases.

Vision impairment and blindness present significant global challenges, with common causes including age-related macular degeneration, diabetes, retinitis pigmentosa, and glaucoma. Advanced imaging tools, such as optical coherence tomography, fundus photography, photoacoustic microscopy, and fluorescence imaging, play a crucial role in improving therapeutic interventions and diagnostic methods. Contrast agents are often employed with these tools to enhance image clarity and signal detection. This review aims to explore the commonly used contrast agents in ocular disease imaging. The first section of the review delves into advanced ophthalmic imaging techniques, outlining their importance in addressing vision-related issues. The emphasis is on the efficacy of therapeutic interventions and diagnostic methods, establishing a foundation for the subsequent exploration of contrast agents. This review focuses on the role of contrast agents, with a specific emphasis on gold nanoparticles, particularly gold nanorods. The discussion highlights how these contrast agents optimize imaging in ocular disease diagnosis and monitoring, emphasizing their unique properties that enhance signal detection and imaging precision. The final section, we explores both organic and inorganic contrast agents and their applications in specific conditions such as choroidal neovascularization, retinal neovascularization, and stem cell tracking. The review concludes by addressing the limitations of current contrast agent usage and discussing potential future clinical applications. This comprehensive exploration contributes to advancing our understanding of contrast agents in ocular disease imaging and sets the stage for further research and development in the field.

Unsupervised Learning for Enhanced Computed Photoacoustic Microscopy

Photoacoustic microscopy (PAM) is a medical-imaging technique with the merits of high contrast and resolution. Nevertheless, conventional PAM scans specimens in a diameter-by-diameter fashion, resulting in a time-consuming process. Furthermore, deep-learning-based PAM image enhancement necessitates acquiring ground-truth data for training purposes. In this paper, we built an optical-resolution photoacoustic microscopy system and introduced an innovative unsupervised-learning algorithm. First, we enhanced the rotational-scanning method, transitioning from a diameter-by-diameter approach to a sector-by-sector one, significantly reducing imaging time (from 280 s to 109 s). Second, by establishing a metric for unsupervised learning, we eliminated the need for collecting reliable and high-quality ground truth, which is a challenging task in photoacoustic microscopy. A total of 324 pairs of datasets (mouse ears) were collected for unsupervised learning, with 274 for training and 50 for testing. Additionally, carbon-fiber data were sampled for lateral resolution and contrast evaluation, as well as the effective rate evaluation of the algorithm. The enhanced images demonstrated superior performance compared with that of maximum projection, both subjectively and objectively. A 76% improvement in the lateral resolution was observed. The effective rate of the algorithm was measured to be 100%, which was tested on 50 random samples. The technique presented in this paper holds substantial potential for image postprocessing and opens new avenues for unsupervised learning in photoacoustic microscopy.

Sounding out the dynamics: a concise review of high-speed photoacoustic microscopy.

Photoacoustic microscopy (PAM) offers advantages in high-resolution and high-contrast imaging of biomedical chromophores. The speed of imaging is critical for leveraging these benefits in both preclinical and clinical settings. Ongoing technological innovations have substantially boosted PAM's imaging speed, enabling real-time monitoring of dynamic biological processes. This concise review synthesizes historical context and current advancements in high-speed PAM, with an emphasis on developments enabled by ultrafast lasers, scanning mechanisms, and advanced imaging processing methods. We examine cutting-edge innovations across multiple facets of PAM, including light sources, scanning and detection systems, and computational techniques and explore their representative applications in biomedical research. This work delineates the challenges that persist in achieving optimal high-speed PAM performance and forecasts its prospective impact on biomedical imaging. Recognizing the current limitations, breaking through the drawbacks, and adopting the optimal combination of each technology will lead to the realization of ultimate high-speed PAM for both fundamental research and clinical translation.

Photoacoustic imaging of squirrel monkey cortical responses induced by peripheral mechanical stimulation.

Non-human primates (NHPs) are crucial models for studies of neuronal activity. Emerging photoacoustic imaging modalities offer excellent tools for studying NHP brains with high sensitivity and high spatial resolution. In this research, a photoacoustic microscopy (PAM) device was used to provide a label-free quantitative characterization of cerebral hemodynamic changes due to peripheral mechanical stimulation. A 5 × 5 mm area within the somatosensory cortex region of an adult squirrel monkey was imaged. A deep, fully connected neural network was characterized and applied to the PAM images of the cortex to enhance the vessel structures after mechanical stimulation on the forelimb digits. The quality of the PAM images was improved significantly with a neural network while preserving the hemodynamic responses. The functional responses to the mechanical stimulation were characterized based on the improved PAM images. This study demonstrates capability of PAM combined with machine learning for functional imaging of the NHP brain.

Photoacoustic Microscopy Imaging for Advanced Biomedical Applications (Invited)

Photoacoustic Microscopy Imaging for Advanced Biomedical Applications (Invited)

Multimodal photoacoustic microscopy, optical coherence tomography, and fluorescence imaging of USH2A knockout rabbits

Usher syndrome type 2A (USH2A) is a genetic disorder characterized by retinal degeneration and hearing loss. To better understand the pathogenesis and progression of this syndrome, animal models such as USH2A knockout (USH2AKO) rabbits have been developed. In this study, we employed multimodal imaging techniques, including photoacoustic microscopy (PAM), optical coherence tomography (OCT), fundus autofluorescence (FAF), fluorescein angiography (FA), and indocyanine green angiography (ICGA) imaging to evaluate the retinal changes in the USH2AKO rabbit model. Twelve New Zealand White rabbits including USH2AKO and wild type (WT) were used for the experiments. Multimodal imaging was implemented at different time points over a period of 12 months to visualize the progression of retinal changes in USH2AKO rabbits. The results demonstrate that ellipsoid zone (EZ) disruption and degeneration, key features of Usher syndrome, began at the age of 4 months old and persisted up to 12 months. The EZ degeneration areas were clearly observed on the FAF and OCT images. The FAF images revealed retinal pigment epithelium (RPE) degeneration, confirming the presence of the disease phenotype in the USH2AKO rabbits. In addition, PAM images provided high-resolution and high image contrast of the optic nerve and the retinal microvasculature, including retinal vessels, choroidal vessels, and capillaries in three-dimensions. The quantification of EZ fluorescent intensity using FAF and EZ thickness using OCT provided comprehensive quantitative data on the progression of degenerative changes over time. This multimodal imaging approach allowed for a comprehensive and non-invasive assessment of retinal structure, microvasculature, and degenerative changes in the USH2AKO rabbit model. The combination of PAM, OCT, and fluorescent imaging facilitated longitudinal monitoring of disease progression and provided valuable insights into the pathophysiology of USH2A syndrome. These findings contribute to the understanding of USH2A syndrome and may have implications for the development of diagnostic and therapeutic strategies for affected individuals. The multimodal imaging techniques employed in this study offer a promising platform for preclinical evaluation of potential treatments and may pave the way for future clinical applications in patients with Usher syndrome.

Quantitative classification of melasma with photoacoustic microscopy: a pilot study.

The classification of melasma is critical for correct clinical diagnosis, treatment selection, and postoperative measures. However, preoperative quantitative determination of melasma type remains challenging using conventional Wood's lamp and optical dermoscopy techniques. Using photoacoustic microscopy (PAM) to simultaneously obtain the two diagnostic indicators of melanin and blood vessels for melasma classification and perform quantitative analysis to finally achieve accurate classification, rather than relying solely on physicians' experience. First, the patients were classified by experienced dermatologists with Wood's lamp and optical dermoscopy. Next, the patients were examined in vivo using the PAM imaging system. Further, the horizontal section images ( plane) of epidermal melanin and dermal vascular involvement were extracted from the 3D photoacoustic imaging results, which are important basis for PAM to quantitatively classify melasma. PAM can quantitatively reveal epidermal thickness and dermal vascular morphology in each case and obtain the quantitative diagnostic indicators of melanin and blood vessels. The mean vascular diameter in lesional skin () of epidermal M+V-type was much larger than that in non-lesional skin (), and the mean vascular density in lesional skin was more than three times that in non-lesional skin. Importantly, vascular diameter and density are important parameters for distinguishing M type from M+V type. PAM can obtain the data of epidermal thickness, pigment depth, subcutaneous vascular diameter, and vascular density, and realize the dual standard quantitative melasma classification by combining the parameters of melanin and blood vessels. In addition, PAM can provide new diagnostic information for uncertain melasma types and further refine the typing.