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Zhang S, Miao J, Li LS. Challenges and advances in two-dimensional photoacoustic computed tomography: a review. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:070901. [PMID: 39006312 PMCID: PMC11245175 DOI: 10.1117/1.jbo.29.7.070901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 07/16/2024]
Abstract
Significance Photoacoustic computed tomography (PACT), a hybrid imaging modality combining optical excitation with acoustic detection, has rapidly emerged as a prominent biomedical imaging technique. Aim We review the challenges and advances of PACT, including (1) limited view, (2) anisotropy resolution, (3) spatial aliasing, (4) acoustic heterogeneity (speed of sound mismatch), and (5) fluence correction of spectral unmixing. Approach We performed a comprehensive literature review to summarize the key challenges in PACT toward practical applications and discuss various solutions. Results There is a wide range of contributions from both industry and academic spaces. Various approaches, including emerging deep learning methods, are proposed to improve the performance of PACT further. Conclusions We outline contemporary technologies aimed at tackling the challenges in PACT applications.
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Affiliation(s)
- Shunyao Zhang
- Rice University, Department of Electrical and Computer Engineering, Houston, Texas, United States
| | - Jingyi Miao
- Rice University, Department of Electrical and Computer Engineering, Houston, Texas, United States
| | - Lei S. Li
- Rice University, Department of Electrical and Computer Engineering, Houston, Texas, United States
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Wang Y, Li C. Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:066006. [PMID: 38846677 PMCID: PMC11155389 DOI: 10.1117/1.jbo.29.6.066006] [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: 02/05/2024] [Revised: 04/30/2024] [Accepted: 05/20/2024] [Indexed: 06/09/2024]
Abstract
Significance Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast imaging speed, modern PACT systems have equipped arrays that have hundreds to thousands of ultrasound transducer (UST) elements, and the element number continues to increase. However, large number of UST elements with parallel data acquisition could generate a massive data size, making it very challenging to realize fast image reconstruction. Although several research groups have developed GPU-accelerated method for PACT, there lacks an explicit and feasible step-by-step description of GPU-based algorithms for various hardware platforms. Aim In this study, we propose a comprehensive framework for developing GPU-accelerated PACT image reconstruction (GPU-accelerated photoacoustic computed tomography), to help the research community to grasp this advanced image reconstruction method. Approach We leverage widely accessible open-source parallel computing tools, including Python multiprocessing-based parallelism, Taichi Lang for Python, CUDA, and possible other backends. We demonstrate that our framework promotes significant performance of PACT reconstruction, enabling faster analysis and real-time applications. Besides, we also described how to realize parallel computing on various hardware configurations, including multicore CPU, single GPU, and multiple GPUs platform. Results Notably, our framework can achieve an effective rate of ∼ 871 times when reconstructing extremely large-scale three-dimensional PACT images on a dual-GPU platform compared to a 24-core workstation CPU. In this paper, we share example codes via GitHub. Conclusions Our approach allows for easy adoption and adaptation by the research community, fostering implementations of PACT for both life science and medicine.
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Affiliation(s)
- Yibing Wang
- Peking University, College of Future Technology, Department of Biomedical Engineering, Beijing, China
| | - Changhui Li
- Peking University, College of Future Technology, Department of Biomedical Engineering, Beijing, China
- Peking University, National Biomedical Imaging Center, Beijing, China
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Yu Y, Feng T, Qiu H, Gu Y, Chen Q, Zuo C, Ma H. Simultaneous photoacoustic and ultrasound imaging: A review. ULTRASONICS 2024; 139:107277. [PMID: 38460216 DOI: 10.1016/j.ultras.2024.107277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/09/2024] [Accepted: 02/26/2024] [Indexed: 03/11/2024]
Abstract
Photoacoustic imaging (PAI) is an emerging biomedical imaging technique that combines the advantages of optical and ultrasound imaging, enabling the generation of images with both optical resolution and acoustic penetration depth. By leveraging similar signal acquisition and processing methods, the integration of photoacoustic and ultrasound imaging has introduced a novel hybrid imaging modality suitable for clinical applications. Photoacoustic-ultrasound imaging allows for non-invasive, high-resolution, and deep-penetrating imaging, providing a wealth of image information. In recent years, with the deepening research and the expanding biomedical application scenarios of photoacoustic-ultrasound bimodal systems, the immense potential of photoacoustic-ultrasound bimodal imaging in basic research and clinical applications has been demonstrated, with some research achievements already commercialized. In this review, we introduce the principles, technical advantages, and biomedical applications of photoacoustic-ultrasound bimodal imaging techniques, specifically focusing on tomographic, microscopic, and endoscopic imaging modalities. Furthermore, we discuss the future directions of photoacoustic-ultrasound bimodal imaging technology.
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Affiliation(s)
- Yinshi Yu
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Ting Feng
- Academy for Engineering & Technology, Fudan University, Shanghai 200433,China.
| | - Haixia Qiu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Ying Gu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Qian Chen
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Chao Zuo
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
| | - Haigang Ma
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
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Tarvainen T, Cox B. Quantitative photoacoustic tomography: modeling and inverse problems. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S11509. [PMID: 38125717 PMCID: PMC10731766 DOI: 10.1117/1.jbo.29.s1.s11509] [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: 09/20/2023] [Revised: 11/19/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
Significance Quantitative photoacoustic tomography (QPAT) exploits the photoacoustic effect with the aim of estimating images of clinically relevant quantities related to the tissue's optical absorption. The technique has two aspects: an acoustic part, where the initial acoustic pressure distribution is estimated from measured photoacoustic time-series, and an optical part, where the distributions of the optical parameters are estimated from the initial pressure. Aim Our study is focused on the optical part. In particular, computational modeling of light propagation (forward problem) and numerical solution methodologies of the image reconstruction (inverse problem) are discussed. Approach The commonly used mathematical models of how light and sound propagate in biological tissue are reviewed. A short overview of how the acoustic inverse problem is usually treated is given. The optical inverse problem and methods for its solution are reviewed. In addition, some limitations of real-life measurements and their effect on the inverse problems are discussed. Results An overview of QPAT with a focus on the optical part was given. Computational modeling and inverse problems of QPAT were addressed, and some key challenges were discussed. Furthermore, the developments for tackling these problems were reviewed. Although modeling of light transport is well-understood and there is a well-developed framework of inverse mathematics for approaching the inverse problem of QPAT, there are still challenges in taking these methodologies to practice. Conclusions Modeling and inverse problems of QPAT together were discussed. The scope was limited to the optical part, and the acoustic aspects were discussed only to the extent that they relate to the optical aspect.
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Affiliation(s)
- Tanja Tarvainen
- University of Eastern Finland, Department of Technical Physics, Kuopio, Finland
| | - Ben Cox
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
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Yip LCM, Rascevska E, Omidi P, Carson JJL. Photoacoustic tomography as a method to estimate the optical fluence distribution in turbid media. BIOMEDICAL OPTICS EXPRESS 2023; 14:5036-5046. [PMID: 37854557 PMCID: PMC10581793 DOI: 10.1364/boe.496078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 07/26/2023] [Accepted: 07/27/2023] [Indexed: 10/20/2023]
Abstract
Currently, there are no non-invasive experimental methods available for measuring optical fluence distributions in tissue. We present photoacoustic tomography (PAT) as a method to approximate the relative optical fluence distribution in a homogeneous optically scattering medium. Three-dimensional photoacoustic images were captured with a near-full view PAT scanner in phantoms with known optical absorption and scatter properties. Resultant 3D PAT images were compared to the expected optical fluence distributions from Monte Carlo simulations and diffusion theory using volumetric and shape analysis. Volumetric analysis of PAT images compared well with the optical fluence distributions from simulation. Dice similarity coefficients ranged from 51 to 82%. The reduced scattering coefficient estimated from PAT images compared well to estimates from simulations for values below 0.5 mm-1. Near full-view PAT has been found to be useful for estimating the optical fluence distribution in an optically scattering medium. Further development is needed to extend the measurement range.
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Affiliation(s)
- Lawrence C. M. Yip
- Lawson Health Research Institute, Imaging Program, 268 Grosvenor St., London, Canada, N6A 4V2, Canada
- Western University, Schulich School of Medicine and Dentistry, Department of Medical Biophysics, 1151 Richmond St, London, Canada, N6A 3K7, Canada
| | - Elina Rascevska
- Lawson Health Research Institute, Imaging Program, 268 Grosvenor St., London, Canada, N6A 4V2, Canada
- Western University, School of Biomedical Engineering, 1151 Richmond St, London, Canada, N6A 3K7, Canada
| | - Parsa Omidi
- Western University, School of Biomedical Engineering, 1151 Richmond St, London, Canada, N6A 3K7, Canada
| | - Jeffrey J. L. Carson
- Lawson Health Research Institute, Imaging Program, 268 Grosvenor St., London, Canada, N6A 4V2, Canada
- Western University, Schulich School of Medicine and Dentistry, Department of Medical Biophysics, 1151 Richmond St, London, Canada, N6A 3K7, Canada
- Western University, School of Biomedical Engineering, 1151 Richmond St, London, Canada, N6A 3K7, Canada
- Western University, Schulich School of Medicine and Dentistry, Department of Surgery, 1151 Richmond St, London, Canada, N6A 3K7, Canada
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Rascevska E, Yip L, Omidi P, Brackstone M, Carson J. Investigating the feasibility of a hand-held photoacoustic imaging probe for margin assessment during breast conserving surgery. PHOTOACOUSTICS 2022; 28:100424. [PMID: 36386296 PMCID: PMC9650058 DOI: 10.1016/j.pacs.2022.100424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/10/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Approximately 19 % of breast cancer patients undergoing breast conserving surgery (BCS) must return for a secondary surgery due to incomplete tumour removal. Our previous work demonstrated that the lower lipid content, characteristic of tumour tissue, was observed as regions of hypo-intense photoacoustic (PA) contrast. The goal of this work was to evaluate feasibility of a low-frequency, hand-held PA imaging probe for surgical margin assessment based on lipid content differences. Here, we describe (i) the design of a prototype hand-held PA imaging probe, (ii) the effect of limited-bandwidth on image contrast, (iii) accuracy towards hypo-intense contrast detection, (iv) the limited-view characteristics of the single sensor design, and (iv) early imaging results of an ex-vivo breast cancer specimen. The probe incorporates a single polyvinylidene fluoride acoustic sensor, a 1-to-4 optical fibre bundle and a polycarbonate axicon lens for light delivery. Imaging results on phantoms designed to mimic positive margins demonstrated the ability to detect gaps in optical absorption as small as 1 mm in width. Compared to images from a near full-view PAI system, the hand-held PAI probe had higher signal to noise ratio but suffered from negativity image artifacts. Lumpectomy specimen imaging showed that strong signals can be obtained from the fatty tissue. Taken together, the results show this imaging approach with a hand-held probe has potential for detection of residual breast cancer tissue during BCS; however, more work is needed to reduce the size of the probe to fit within the surgical cavity.
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Affiliation(s)
- E. Rascevska
- Imaging Program, Lawson Health Research Institute, 268 Grosvenor St., London N6A 4V2, ON, Canada
- School of Biomedical Engineering, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
| | - L.C.M. Yip
- Imaging Program, Lawson Health Research Institute, 268 Grosvenor St., London N6A 4V2, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
| | - P. Omidi
- Imaging Program, Lawson Health Research Institute, 268 Grosvenor St., London N6A 4V2, ON, Canada
- School of Biomedical Engineering, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
| | - M. Brackstone
- Department of Surgery, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
- Department of Oncology, Schulich School of Medicine & Dentistry, The University of Western Ontario, 1151 Richmond St., N6A 3K7, London, ON, Canada
| | - J.J.L. Carson
- Imaging Program, Lawson Health Research Institute, 268 Grosvenor St., London N6A 4V2, ON, Canada
- School of Biomedical Engineering, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
- Department of Surgery, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond St., London N6A 3K7, ON, Canada
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