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Wang Z, Chen Y, Pan S, Zhang W, Guo Z, Wang Y, Yang S. Quantitative classification of melasma with photoacoustic microscopy: a pilot study. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S11504. [PMID: 37927370 PMCID: PMC10624224 DOI: 10.1117/1.jbo.29.s1.s11504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 10/15/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023]
Abstract
Significance 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. Aim 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. Approach 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 (X - Y 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. Results 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 (223.2 μ m ) of epidermal M+V-type was much larger than that in non-lesional skin (131.6 μ m ), 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. Conclusions 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.
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Affiliation(s)
- Zhiyang Wang
- South China Normal University, Institute of Laser Life Science, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
- South China Normal University, College of Biophotonics, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou, China
| | - Yuying Chen
- South China Normal University, Institute of Laser Life Science, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
- South China Normal University, College of Biophotonics, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou, China
| | - Shu Pan
- South China Normal University, Institute of Laser Life Science, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
- South China Normal University, College of Biophotonics, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou, China
| | - Wuyu Zhang
- South China Normal University, Institute of Laser Life Science, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
- South China Normal University, College of Biophotonics, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou, China
- Guangdong Photoacoustic Technology Co., Ltd., Foshan, China
| | - Ziwei Guo
- Zhujiang Hospital of Southern Medical University, Department of Plastic Surgery, Guangzhou, China
| | - Yuzhi Wang
- General Hospital of Southern Theater Command, Department of Burns and Plastic Surgery, Guangzhou, China
| | - Sihua Yang
- South China Normal University, Institute of Laser Life Science, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
- South China Normal University, College of Biophotonics, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou, China
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Cho SW, Nguyen VT, DiSpirito A, Yang J, Kim CS, Yao J. Sounding out the dynamics: a concise review of high-speed photoacoustic microscopy. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S11521. [PMID: 38323297 PMCID: PMC10846286 DOI: 10.1117/1.jbo.29.s1.s11521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/15/2023] [Accepted: 01/11/2024] [Indexed: 02/08/2024]
Abstract
Significance 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. Aim 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. Approach 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. Results This work delineates the challenges that persist in achieving optimal high-speed PAM performance and forecasts its prospective impact on biomedical imaging. Conclusions 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.
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Affiliation(s)
- Soon-Woo Cho
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Pusan National University, Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology, Busan, Republic of Korea
| | - Van Tu Nguyen
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Anthony DiSpirito
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Joseph Yang
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Chang-Seok Kim
- Pusan National University, Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology, Busan, Republic of Korea
| | - Junjie Yao
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
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Jiang D, Zhu L, Tong S, Shen Y, Gao F, Gao F. Photoacoustic imaging plus X: a review. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S11513. [PMID: 38156064 PMCID: PMC10753847 DOI: 10.1117/1.jbo.29.s1.s11513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/14/2023] [Accepted: 12/11/2023] [Indexed: 12/30/2023]
Abstract
Significance Photoacoustic (PA) imaging (PAI) represents an emerging modality within the realm of biomedical imaging technology. It seamlessly blends the wealth of optical contrast with the remarkable depth of penetration offered by ultrasound. These distinctive features of PAI hold tremendous potential for various applications, including early cancer detection, functional imaging, hybrid imaging, monitoring ablation therapy, and providing guidance during surgical procedures. The synergy between PAI and other cutting-edge technologies not only enhances its capabilities but also propels it toward broader clinical applicability. Aim The integration of PAI with advanced technology for PA signal detection, signal processing, image reconstruction, hybrid imaging, and clinical applications has significantly bolstered the capabilities of PAI. This review endeavor contributes to a deeper comprehension of how the synergy between PAI and other advanced technologies can lead to improved applications. Approach An examination of the evolving research frontiers in PAI, integrated with other advanced technologies, reveals six key categories named "PAI plus X." These categories encompass a range of topics, including but not limited to PAI plus treatment, PAI plus circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. Results After conducting a comprehensive review of the existing literature and research on PAI integrated with other technologies, various proposals have emerged to advance the development of PAI plus X. These proposals aim to enhance system hardware, improve imaging quality, and address clinical challenges effectively. Conclusions The progression of innovative and sophisticated approaches within each category of PAI plus X is positioned to drive significant advancements in both the development of PAI technology and its clinical applications. Furthermore, PAI not only has the potential to integrate with the above-mentioned technologies but also to broaden its applications even further.
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Affiliation(s)
- Daohuai Jiang
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
- Fujian Normal University, College of Photonic and Electronic Engineering, Fuzhou, China
| | - Luyao Zhu
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
| | - Shangqing Tong
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
| | - Yuting Shen
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
| | - Feng Gao
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
| | - Fei Gao
- ShanghaiTech University, School of Information Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, Shanghai, China
- Shanghai Clinical Research and Trial Center, Shanghai, China
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Guo T, Xiong K, Yuan B, Zhang Z, Wang L, Zhang Y, Liang C, Liu Z. Homogeneous-resolution photoacoustic microscopy for ultrawide field-of-view neurovascular imaging in Alzheimer's disease. PHOTOACOUSTICS 2023; 31:100516. [PMID: 37313359 PMCID: PMC10258506 DOI: 10.1016/j.pacs.2023.100516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 05/25/2023] [Accepted: 05/25/2023] [Indexed: 06/15/2023]
Abstract
Neurovascular imaging is essential for investigating neurodegenerative diseases. However, the existing neurovascular imaging technology suffers from a trade-off between a field of view (FOV) and resolution in the whole brain, resulting in an inhomogeneous resolution and lack of information. Here, homogeneous-resolution arched-scanning photoacoustic microscopy (AS-PAM), which has an ultrawide FOV to cover the entire mouse cerebral cortex, was developed. Imaging of the neurovasculature was performed with a homogenous resolution of 6.9 µm from the superior sagittal sinus to the middle cerebral artery and caudal rhinal vein in an FOV of 12 × 12 mm2. Moreover, using AS-PAM, vascular features of the meninges and cortex were quantified in early Alzheimer's disease (AD) and wild-type (WT) mice. The results demonstrated high sensitivity to the pathological progression of AD on tortuosity and branch index. The high-fidelity imaging capability in large FOV enables AS-PAM to be a promising tool for precise brain neurovascular visualization and quantification.
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Affiliation(s)
- Ting Guo
- School of Medicine South China University of Technology, Guangzhou 510006, China
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou 510080, China
| | - Kedi Xiong
- MOE Key Laboratory of Laser Life Science Institute of Laser Life Science, South China Normal University, Guangzhou 510631, China
- Guangdong Provincial Key Laboratory of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631, China
| | - Bo Yuan
- MOE Key Laboratory of Laser Life Science Institute of Laser Life Science, South China Normal University, Guangzhou 510631, China
- Guangdong Provincial Key Laboratory of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631, China
| | - Zhenhui Zhang
- MOE Key Laboratory of Laser Life Science Institute of Laser Life Science, South China Normal University, Guangzhou 510631, China
- Guangdong Provincial Key Laboratory of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631, China
| | - Lijuan Wang
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China
- Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangzhou 510080, China
| | - Yuhu Zhang
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China
- Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangzhou 510080, China
| | - Changhong Liang
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou 510080, China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou 510080, China
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Cao R, Zhao J, Li L, Du L, Zhang Y, Luo Y, Jiang L, Davis S, Zhou Q, de la Zerda A, Wang LV. Optical-resolution photoacoustic microscopy with a needle-shaped beam. NATURE PHOTONICS 2023; 17:89-95. [PMID: 38149029 PMCID: PMC10751030 DOI: 10.1038/s41566-022-01112-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/19/2022] [Indexed: 12/28/2023]
Abstract
Optical-resolution photoacoustic microscopy (OR-PAM) can visualize wavelength-dependent optical absorption at the cellular level. However, OR-PAM suffers from a limited depth of field (DOF) due to the tight focus of the optical excitation beam, making it challenging to acquire high-resolution images of samples with uneven surfaces or high-quality volumetric images without z-scanning. To overcome this limitation, we propose needle-shaped beam photoacoustic microscopy (NB-PAM), which can extend the DOF to up to ~28-fold Rayleigh lengths via customized diffractive optical elements (DOEs). The DOE generate a needle beam with a well-maintained beam diameter, a uniform axial intensity distribution, and negligible sidelobes. The advantage of using NB-PAM is demonstrated by both histology-like imaging of fresh slide-free organs using a 266 nm laser and in vivo mouse brain vasculature imaging using a 532 nm laser. The approach provides new perspectives for slide-free intraoperative pathological imaging and in-vivo organ-level imaging.
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Affiliation(s)
- Rui Cao
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Jingjing Zhao
- Department of Structural Biology, Stanford University School of Medicine, Stanford University, Stanford, California, USA
| | - Lei Li
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Lin Du
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Yide Zhang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Yilin Luo
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Laiming Jiang
- Department of Biomedical Engineering and Ophthalmology, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Samuel Davis
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Qifa Zhou
- Department of Biomedical Engineering and Ophthalmology, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Adam de la Zerda
- Department of Structural Biology, Stanford University School of Medicine, Stanford University, Stanford, California, USA
- Biophysics Program, Molecular Imaging Program, and Bio-X Program at Stanford University, Stanford, California, USA
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Lihong V Wang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, California, USA
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