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Nyayapathi N, Zheng E, Zhou Q, Doyley M, Xia J. Dual-modal Photoacoustic and Ultrasound Imaging: from preclinical to clinical applications. FRONTIERS IN PHOTONICS 2024; 5:1359784. [PMID: 39185248 PMCID: PMC11343488 DOI: 10.3389/fphot.2024.1359784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Photoacoustic imaging is a novel biomedical imaging modality that has emerged over the recent decades. Due to the conversion of optical energy into the acoustic wave, photoacoustic imaging offers high-resolution imaging in depth beyond the optical diffusion limit. Photoacoustic imaging is frequently used in conjunction with ultrasound as a hybrid modality. The combination enables the acquisition of both optical and acoustic contrasts of tissue, providing functional, structural, molecular, and vascular information within the same field of view. In this review, we first described the principles of various photoacoustic and ultrasound imaging techniques and then classified the dual-modal imaging systems based on their preclinical and clinical imaging applications. The advantages of dual-modal imaging were thoroughly analyzed. Finally, the review ends with a critical discussion of existing developments and a look toward the future.
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Affiliation(s)
- Nikhila Nyayapathi
- Electrical and Computer Engineering, University of Rochester, Rochester, New York, 14627
| | - Emily Zheng
- Department of Biomedical Engineering, University at Buffalo, Buffalo, New York, 14226
| | - Qifa Zhou
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90007
| | - Marvin Doyley
- Electrical and Computer Engineering, University of Rochester, Rochester, New York, 14627
| | - Jun Xia
- Department of Biomedical Engineering, University at Buffalo, Buffalo, New York, 14226
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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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Gu L, Deng H, Bai Y, Gao J, Wang X, Yue T, Luo B, Ma C. Sentinel lymph node mapping in patients with breast cancer using a photoacoustic/ultrasound dual-modality imaging system with carbon nanoparticles as the contrast agent: a pilot study. BIOMEDICAL OPTICS EXPRESS 2023; 14:1003-1014. [PMID: 36950229 PMCID: PMC10026566 DOI: 10.1364/boe.482126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 01/12/2023] [Accepted: 01/12/2023] [Indexed: 06/18/2023]
Abstract
Assessing the metastatic status of axillary lymph nodes is a common clinical practice in the staging of early breast cancers. Yet sentinel lymph nodes (SLNs) are the regional lymph nodes believed to be the first stop along the lymphatic drainage path of the metastasizing cancer cells. Compared to axillary lymph node dissection, sentinel lymph node biopsy (SLNB) helps reduce morbidity and side effects. Current SLNB methods, however, still have suboptimum properties, such as restrictions due to nuclide accessibility and a relatively low therapeutic efficacy when only a single contrast agent is used. To overcome these limitations, researchers have been motivated to develop a non-radioactive SLN mapping method to replace or supplement radionuclide mapping. We proposed and demonstrated a clinical procedure using a dual-modality photoacoustic (PA)/ultrasound (US) imaging system to locate the SLNs to offer surgical guidance. In our work, the high contrast of PA imaging and its specificity to SLNs were based on the accumulation of carbon nanoparticles (CNPs) in the SLNs. A machine-learning model was also trained and validated to distinguish stained SLNs based on single-wavelength PA images. In the pilot study, we imaged 11 patients in vivo, and the specimens from 13 patients were studied ex vivo. PA/US imaging identified stained SLNs in vivo without a single false positive (23 SLNs), yielding 100% specificity and 52.6% sensitivity based on the current PA imaging system. Our machine-learning model can automatically detect SLNs in real time. In the new procedure, single-wavelength PA/US imaging uses CNPs as the contrast agent. The new system can, with that contrast agent, noninvasively image SLNs with high specificity in real time based on the unique features of the SLNs in the PA images. Ultimately, we aim to use our systems and approach to substitute or supplement nuclide tracers for a non-radioactive, less invasive SLN mapping method in SLNB for the axillary staging of breast cancer.
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Affiliation(s)
- Liujie Gu
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
- Institute for Intelligent Healthcare, Tsinghua University, Beijing 100084, China
- These authors contributed equally to this work
| | - Handi Deng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
- These authors contributed equally to this work
| | - Yizhou Bai
- Institute for Intelligent Healthcare, Tsinghua University, Beijing 100084, China
- Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
- These authors contributed equally to this work
| | - Jianpan Gao
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
| | - Xuewei Wang
- Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
| | - Tong Yue
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
| | - Bin Luo
- Institute for Intelligent Healthcare, Tsinghua University, Beijing 100084, China
- Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
- Co-last authors
| | - Cheng Ma
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
- Institute for Intelligent Healthcare, Tsinghua University, Beijing 100084, China
- Co-last authors
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Choi W, Park B, Choi S, Oh D, Kim J, Kim C. Recent Advances in Contrast-Enhanced Photoacoustic Imaging: Overcoming the Physical and Practical Challenges. Chem Rev 2023. [PMID: 36642892 DOI: 10.1021/acs.chemrev.2c00627] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
For decades now, photoacoustic imaging (PAI) has been investigated to realize its potential as a niche biomedical imaging modality. Despite its highly desirable optical contrast and ultrasonic spatiotemporal resolution, PAI is challenged by such physical limitations as a low signal-to-noise ratio (SNR), diminished image contrast due to strong optical attenuation, and a lower-bound on spatial resolution in deep tissue. In addition, contrast-enhanced PAI has faced practical limitations such as insufficient cell-specific targeting due to low delivery efficiency and difficulties in developing clinically translatable agents. Identifying these limitations is essential to the continuing expansion of the field, and substantial advances in developing contrast-enhancing agents, complemented by high-performance image acquisition systems, have synergistically dealt with the challenges of conventional PAI. This review covers the past four years of research on pushing the physical and practical challenges of PAI in terms of SNR/contrast, spatial resolution, targeted delivery, and clinical application. Promising strategies for dealing with each challenge are reviewed in detail, and future research directions for next generation contrast-enhanced PAI are discussed.
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Affiliation(s)
- Wonseok Choi
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Byullee Park
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Seongwook Choi
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Donghyeon Oh
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Jongbeom Kim
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Chulhong Kim
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
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Zheng W, Zhang H, Huang C, McQuillan K, Li H, Xu W, Xia J. Deep-E Enhanced Photoacoustic Tomography Using Three-Dimensional Reconstruction for High-Quality Vascular Imaging. SENSORS (BASEL, SWITZERLAND) 2022; 22:7725. [PMID: 36298076 PMCID: PMC9606963 DOI: 10.3390/s22207725] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/30/2022] [Accepted: 10/09/2022] [Indexed: 06/01/2023]
Abstract
Linear-array-based photoacoustic computed tomography (PACT) has been widely used in vascular imaging due to its low cost and high compatibility with current ultrasound systems. However, linear-array transducers have inherent limitations for three-dimensional imaging due to the poor elevation resolution. In this study, we introduced a deep learning-assisted data process algorithm to enhance the image quality in linear-array-based PACT. Compared to our earlier study where training was performed on 2D reconstructed data, here, we utilized 2D and 3D reconstructed data to train the two networks separately. We then fused the image data from both 2D and 3D training to get features from both algorithms. The numerical and in vivo validations indicate that our approach can improve elevation resolution, recover the true size of the object, and enhance deep vessels. Our deep learning-assisted approach can be applied to translational imaging applications that require detailed visualization of vascular features.
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Affiliation(s)
- Wenhan Zheng
- Department of Biomedical Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Huijuan Zhang
- Department of Biomedical Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Chuqin Huang
- Department of Biomedical Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Kaylin McQuillan
- Department of Biomedical Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Huining Li
- Department of Computer Science and Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Wenyao Xu
- Department of Computer Science and Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
| | - Jun Xia
- Department of Biomedical Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
- Department of Computer Science and Engineering, University at Buffalo North Campus, Buffalo, NY 14260, USA
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Zheng E, Zhang H, Hu W, Doyley MM, Xia J. Volumetric tri-modal imaging with combined photoacoustic, ultrasound, and shear wave elastography. JOURNAL OF APPLIED PHYSICS 2022; 132:034902. [PMID: 35855685 PMCID: PMC9288268 DOI: 10.1063/5.0093619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
Photoacoustic imaging is a hybrid imaging approach that combines the advantages of optical and ultrasonic imaging in one modality. However, for comprehensive tissue characterization, optical contrast alone is not always sufficient. In this study, we combined photoacoustic imaging with high-resolution ultrasound and shear wave elastography. The multi-modal system can calculate optical absorption, acoustic reflection, and stiffness volumetrically. We constructed a multi-modal phantom with contrast for each imaging modality to test the system's performance. Experimental results indicate that the system successfully visualizes the embedded structures. We envision that the system will lead to more comprehensive tissue characterization for cancer screening and diagnosis.
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Affiliation(s)
- Emily Zheng
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
| | - Huijuan Zhang
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
| | - Wentao Hu
- Department of Electrical and Computer Engineering, Rochester Center for Biomedical Ultrasound, University of Rochester, Rochester, New York 14627, USA
| | - Marvin M. Doyley
- Department of Electrical and Computer Engineering, Rochester Center for Biomedical Ultrasound, University of Rochester, Rochester, New York 14627, USA
| | - Jun Xia
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
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