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Liang Z, Zhang S, Liang Z, Mo Z, Zhang X, Zhong Y, Chen W, Qi L. Deep learning acceleration of iterative model-based light fluence correction for photoacoustic tomography. PHOTOACOUSTICS 2024; 37:100601. [PMID: 38516295 PMCID: PMC10955667 DOI: 10.1016/j.pacs.2024.100601] [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] [Indexed: 03/23/2024]
Abstract
Photoacoustic tomography (PAT) is a promising imaging technique that can visualize the distribution of chromophores within biological tissue. However, the accuracy of PAT imaging is compromised by light fluence (LF), which hinders the quantification of light absorbers. Currently, model-based iterative methods are used for LF correction, but they require extensive computational resources due to repeated LF estimation based on differential light transport models. To improve LF correction efficiency, we propose to use Fourier neural operator (FNO), a neural network specially designed for estimating partial differential equations, to learn the forward projection of light transport in PAT. Trained using paired finite-element-based LF simulation data, our FNO model replaces the traditional computational heavy LF estimator during iterative correction, such that the correction procedure is considerably accelerated. Simulation and experimental results demonstrate that our method achieves comparable LF correction quality to traditional iterative methods while reducing the correction time by over 30 times.
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Affiliation(s)
- Zhaoyong Liang
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Shuangyang Zhang
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Zhichao Liang
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Zongxin Mo
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Xiaoming Zhang
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Yutian Zhong
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Wufan Chen
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
| | - Li Qi
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China
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Suhonen M, Pulkkinen A, Tarvainen T. Single-stage approach for estimating optical parameters in spectral quantitative photoacoustic tomography. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2024; 41:527-542. [PMID: 38437444 DOI: 10.1364/josaa.518768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 01/28/2024] [Indexed: 03/06/2024]
Abstract
In quantitative photoacoustic tomography, the optical parameters of a target, most importantly the concentrations of chromophores such as deoxygenated and oxygenated hemoglobin, are estimated from photoacoustic data measured on the boundary of the target. In this work, a numerical approximation of a forward model for spectral quantitative photoacoustic tomography is constructed by utilizing the diffusion approximation for light propagation, the acoustic wave equation for ultrasound propagation, and spectral models of optical absorption and scattering to describe the wavelength dependence of the optical parameters. The related inverse problem is approached in the framework of Bayesian inverse problems. Concentrations of four chromophores (deoxygenated and oxygenated hemoglobin, water, and lipid), two scattering parameters (reference scattering and scattering power), and the Grüneisen parameter are estimated in a single-stage from photoacoustic data. The methodology is evaluated using numerical simulations in different full-view and limited-view imaging settings. The results show that, utilizing spectral data and models, the spectral optical parameters and the Grüneisen parameter can be simultaneously estimated. Furthermore, the approach can also be utilized in limited-view imaging situations.
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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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Zhang S, Liu J, Liang Z, Ge J, Feng Y, Chen W, Qi L. Pixel-wise reconstruction of tissue absorption coefficients in photoacoustic tomography using a non-segmentation iterative method. PHOTOACOUSTICS 2022; 28:100390. [PMID: 36051488 PMCID: PMC9424605 DOI: 10.1016/j.pacs.2022.100390] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 06/30/2022] [Accepted: 08/14/2022] [Indexed: 06/15/2023]
Abstract
In Photoacoustic Tomography (PAT), the acquired image represents a light energy deposition map of the imaging object. For quantitative imaging, the PAT image is converted into an absorption coefficient (μ a ) map by dividing the light fluence (LF). Previous methods usually assume a uniform tissueμ a distribution, and consequently degrade the LF correction results. Here, we propose a simple method to reconstruct the pixel-wiseμ a map. Our method is based on a non-segmentation-based iterative algorithm, which alternately optimizes the LF distribution and theμ a map. Using simulation data, as well as phantom and animal data, we implemented our algorithm and compared it to segmentation-based correction methods. The results show that our method can obtain accurate estimation of the LF distribution and therefore improve the image quality and feature visibility of theμ a map. Our method may facilitate efficient calculation of the concentration distributions of endogenous and exogenous agents in vivo.
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Affiliation(s)
- Shuangyang Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Jiaming Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhichao Liang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Jia Ge
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Wufan Chen
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
| | - Li Qi
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China
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Zuo H, Cui M, Wang X, Ma C. Spectral crosstalk in photoacoustic computed tomography. PHOTOACOUSTICS 2022; 26:100356. [PMID: 35574185 PMCID: PMC9095891 DOI: 10.1016/j.pacs.2022.100356] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/04/2022] [Accepted: 04/11/2022] [Indexed: 06/15/2023]
Abstract
Multispectral photoacoustic (PA) imaging faces two major challenges: the spectral coloring effect, which has been studied extensively as an optical inversion problem, and the spectral crosstalk, which is basically a result of non-ideal acoustic inversion. So far, there is no systematic work to analyze the spectral crosstalk because acoustic inversion and spectroscopic measurement are always treated as decoupled. In this work, we theorize and demonstrate through a series of simulations and experiments how imperfect acoustic inversion induces inaccurate PA spectrum measurement. We provide detailed analysis to elucidate how different factors, including limited bandwidth, limited view, light attenuation, out-of-plane signal, and image reconstruction schemes, conspire to render the measured PA spectrum inaccurate. We found that the model-based reconstruction outperforms universal back-projection in suppressing the spectral crosstalk in some cases.
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Affiliation(s)
- Hongzhi Zuo
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Manxiu Cui
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Xuanhao Wang
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Cheng Ma
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
- Center for Clinical Big Data Research, Institute of Precision Medicine, Tsinghua University, Beijing 100084, China
- Photomedicine Laboratory, Institute of Precision Medicine, Tsinghua University, Beijing 100084, China
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6
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Hänninen N, Pulkkinen A, Arridge S, Tarvainen T. Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:083013. [PMID: 35396833 PMCID: PMC8993421 DOI: 10.1117/1.jbo.27.8.083013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE The image reconstruction problem in quantitative photoacoustic tomography (QPAT) is an ill-posed inverse problem. Monte Carlo method for light transport can be utilized in solving this image reconstruction problem. AIM The aim was to develop an adaptive image reconstruction method where the number of photon packets in Monte Carlo simulation is varied to achieve a sufficient accuracy with reduced computational burden. APPROACH The image reconstruction problem was formulated as a minimization problem. An adaptive stochastic Gauss-Newton (A-SGN) method combined with Monte Carlo method for light transport was developed. In the algorithm, the number of photon packets used on Gauss-Newton (GN) iteration was varied utilizing a so-called norm test. RESULTS The approach was evaluated with numerical simulations. With the proposed approach, the number of photon packets needed for solving the inverse problem was significantly smaller than in a conventional approach where the number of photon packets was fixed for each GN iteration. CONCLUSIONS The A-SGN method with a norm test can be utilized in QPAT to provide accurate and computationally efficient solutions.
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Affiliation(s)
- Niko Hänninen
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
| | - Aki Pulkkinen
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
| | - Simon Arridge
- University College London, Department of Computer Science, London, United Kingdom
| | - Tanja Tarvainen
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
- University College London, Department of Computer Science, London, United Kingdom
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7
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Quantitative Photoacoustic Reconstruction of the Optical Properties of Intervertebral Discs Using a Gradient Descent Scheme. PHOTONICS 2022. [DOI: 10.3390/photonics9020116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The intervertebral discs (IVD) are among the essential organs of the human body, ensuring the mobility of the spine. These organs possess a high proportion of water. However, as the discs age, this content decreases, which can potentially lead to various diseases called degenerative disc diseases. This water content is therefore an important indicator of the well-being of the disc. In this paper, we propose photoacoustic imaging as a means of probing a disc and quantitatively recovering its molecular composition, which should allow concluding on its state. An adjoint-assisted gradient descent scheme is implemented to recover the optical absorption coefficient in the disc, from which, if spectroscopic measurements are performed, the molecular composition can be deduced. The algorithm was tested on synthetic measurements. A realistic numerical phantom was built from magnetic resonance imaging of an actual IVD of a pig. A simplified experiment, with a single laser source, was performed. Results show the feasibility of using photoacoustics imaging to probe IVDs. The influences of exact and approximate formulations of the gradient are studied. The impact of noise on the reconstructions is also evaluated.
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8
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Wang Y, Xu M, Gao F, Kang F, Zhu S. Nonlinear iterative perturbation scheme with simplified spherical harmonics (SP 3 ) light propagation model for quantitative photoacoustic tomography. JOURNAL OF BIOPHOTONICS 2021; 14:e202000446. [PMID: 33576563 DOI: 10.1002/jbio.202000446] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 01/31/2021] [Accepted: 02/06/2021] [Indexed: 06/12/2023]
Abstract
When using quantitative photoacoustic tomography (q-PAT) reconstruction to recover the optical absorption coefficients of tissue, the commonly used diffusion equation has several limitations in the case of the objects that have small geometries and high-absorption or low-scattering areas. Furthermore, the conventional perturbation reconstruction strategy is unsatisfactory when the target tissue containing large heterogeneous features. We herein present a modified q-PAT implementation that employs the higher-order photon migration model achieving the tradeoff between mathematical rigidity and computational efficiency. Besides, a nonlinear iterative method is proposed to obtain the perturbations of optical absorption considering the updating of the sensitivity matrix in calculating the fluence perturbations. Consequently, the distribution of tissue optical properties can be recovered in a robust way even if the targets with high absorption are included. The proposed approach has been validated by simulation, phantom and in vivo experiments, exhibiting promising performances in image fidelity and quantitative feasibility for practical applications.
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Affiliation(s)
- Yihan Wang
- School of Life Science and Technology, Xidian University, Xi'an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi'an, China
| | - Menglu Xu
- School of Life Science and Technology, Xidian University, Xi'an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi'an, China
| | - Feng Gao
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin University, Tianjin, China
| | - Fei Kang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Shouping Zhu
- School of Life Science and Technology, Xidian University, Xi'an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi'an, China
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Jeng GS, Li ML, Kim M, Yoon SJ, Pitre JJ, Li DS, Pelivanov I, O’Donnell M. Real-time interleaved spectroscopic photoacoustic and ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction. Nat Commun 2021; 12:716. [PMID: 33514737 PMCID: PMC7846772 DOI: 10.1038/s41467-021-20947-5] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 12/22/2020] [Indexed: 02/06/2023] Open
Abstract
For over two decades photoacoustic imaging has been tested clinically, but successful human trials have been limited. To enable quantitative clinical spectroscopy, the fundamental issues of wavelength-dependent fluence variations and inter-wavelength motion must be overcome. Here we propose a real-time, spectroscopic photoacoustic/ultrasound (PAUS) imaging approach using a compact, 1-kHz rate wavelength-tunable laser. Instead of illuminating tissue over a large area, the fiber-optic delivery system surrounding an US array sequentially scans a narrow laser beam, with partial PA image reconstruction for each laser pulse. The final image is then formed by coherently summing partial images. This scheme enables (i) automatic compensation for wavelength-dependent fluence variations in spectroscopic PA imaging and (ii) motion correction of spectroscopic PA frames using US speckle tracking in real-time systems. The 50-Hz video rate PAUS system is demonstrated in vivo using a murine model of labelled drug delivery.
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Affiliation(s)
- Geng-Shi Jeng
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA ,grid.260539.b0000 0001 2059 7017Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan
| | - Meng-Lin Li
- grid.38348.340000 0004 0532 0580Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan ,grid.38348.340000 0004 0532 0580Institute of Photonics Technologies, National Tsing Hua University, Hsinchu, Taiwan
| | - MinWoo Kim
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA
| | - Soon Joon Yoon
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA
| | - John J. Pitre
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA
| | - David S. Li
- grid.34477.330000000122986657Department of Chemical Engineering, University of Washington, Seattle, WA USA
| | - Ivan Pelivanov
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA
| | - Matthew O’Donnell
- grid.34477.330000000122986657Department of Bioengineering, University of Washington, Seattle, WA USA
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Leino AA, Lunttila T, Mozumder M, Pulkkinen A, Tarvainen T. Perturbation Monte Carlo Method for Quantitative Photoacoustic Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:2985-2995. [PMID: 32217473 DOI: 10.1109/tmi.2020.2983129] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Quantitative photoacoustic tomography aims at estimating optical parameters from photoacoustic images that are formed utilizing the photoacoustic effect caused by the absorption of an externally introduced light pulse. This optical parameter estimation is an ill-posed inverse problem, and thus it is sensitive to measurement and modeling errors. In this work, we propose a novel way to solve the inverse problem of quantitative photoacoustic tomography based on the perturbation Monte Carlo method. Monte Carlo method for light propagation is a stochastic approach for simulating photon trajectories in a medium with scattering particles. It is widely accepted as an accurate method to simulate light propagation in tissues. Furthermore, it is numerically robust and easy to implement. Perturbation Monte Carlo maintains this robustness and enables forming gradients for the solution of the inverse problem. We validate the method and apply it in the framework of Bayesian inverse problems. The simulations show that the perturbation Monte Carlo method can be used to estimate spatial distributions of both absorption and scattering parameters simultaneously. These estimates are qualitatively good and quantitatively accurate also in parameter scales that are realistic for biological tissues.
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Kim M, Jeng GS, O’Donnell M, Pelivanov I. Correction of wavelength-dependent laser fluence in swept-beam spectroscopic photoacoustic imaging with a hand-held probe. PHOTOACOUSTICS 2020; 19:100192. [PMID: 32670789 PMCID: PMC7339128 DOI: 10.1016/j.pacs.2020.100192] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/16/2020] [Accepted: 05/16/2020] [Indexed: 05/11/2023]
Abstract
Recently, we demonstrated an integrated photoacoustic (PA) and ultrasound (PAUS) system using a kHz-rate wavelength-tunable laser and a swept-beam delivery approach. It irradiates a medium using a narrow laser beam swept at high repetition rate (∼1 kHz) over the desired imaging area, in contrast to the conventional PA approach using broad-beam illumination at a low repetition rate (10-50 Hz). Here, we present a method to correct the wavelength-dependent fluence distribution and demonstrate its performance in phantom studies using a conventional limited view/bandwidth hand-held US probe. We adopted analytic fluence models, extending diffusion theory for the case of a pencil beam obliquely incident on an optically homogenous turbid medium, and developed a robust method to estimate fluence attenuation in the medium using PA measurements acquired from multiple fiber-irradiation positions swept at a kHz rate. We conducted comprehensive simulation tests and phantom studies using well-known contrast-agents to validate the reliability of the fluence model and its spectral corrections.
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Affiliation(s)
- MinWoo Kim
- Department of Bioengineering, University of Washington, Seattle, WA, 98105, USA
| | - Geng-Shi Jeng
- Department of Electronics Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
| | - Matthew O’Donnell
- Department of Bioengineering, University of Washington, Seattle, WA, 98105, USA
| | - Ivan Pelivanov
- Department of Bioengineering, University of Washington, Seattle, WA, 98105, USA
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12
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Zhou X, Akhlaghi N, Wear KA, Garra BS, Pfefer TJ, Vogt WC. Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging. PHOTOACOUSTICS 2020; 19:100181. [PMID: 32405456 PMCID: PMC7210453 DOI: 10.1016/j.pacs.2020.100181] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 04/03/2020] [Accepted: 04/07/2020] [Indexed: 05/07/2023]
Abstract
Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic diffusion approximation, Monte Carlo simulations, and an algorithm we developed based on novel application of the diffusion dipole model (DDM). Phantoms simulated a range of breast-mimicking optical properties and contained channels filled with chromophore solutions (ink, hemoglobin, or copper sulfate) or connected to a previously developed blood flow circuit providing tunable oxygen saturation (SO2). The DDM algorithm achieved similar spectral recovery and SO2 measurement accuracy to Monte Carlo-based corrections with lower computational cost, potentially providing an accurate, real-time correction approach. Algorithms were sensitive to optical property uncertainty, but error was minimized by matching phantom albedo. The developed test methods may provide a foundation for standardized assessment of MPAI fluence correction algorithm performance.
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Affiliation(s)
- Xuewen Zhou
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, 02742, United States
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
| | - Nima Akhlaghi
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
| | - Keith A. Wear
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
| | - Brian S. Garra
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
| | - T. Joshua Pfefer
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
| | - William C. Vogt
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, United States
- Corresponding author.
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13
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Macdonald CM, Arridge S, Powell S. Efficient inversion strategies for estimating optical properties with Monte Carlo radiative transport models. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200101R. [PMID: 32798354 PMCID: PMC7426481 DOI: 10.1117/1.jbo.25.8.085002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 07/23/2020] [Indexed: 06/11/2023]
Abstract
SIGNIFICANCE Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop an approach to reduce this bottleneck, which has significant implications for quantitative tomographic imaging in a variety of medical and industrial applications. AIM Our aim is to enable computationally efficient image reconstruction in (hybrid) diffuse optical modalities using stochastic forward models. APPROACH Using Monte Carlo, we compute a fully stochastic gradient of an objective function for a given imaging problem. Leveraging techniques from the machine learning community, we then adaptively control the accuracy of this gradient throughout the iterative inversion scheme to substantially reduce computational resources at each step. RESULTS For example problems of quantitative photoacoustic tomography and ultrasound-modulated optical tomography, we demonstrate that solutions are attainable using a total computational expense that is comparable to (or less than) that which is required for a single high-accuracy forward run of the same Monte Carlo model. CONCLUSIONS This approach demonstrates significant computational savings when approaching the full nonlinear inverse problem of optical property estimation using stochastic methods.
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Affiliation(s)
- Callum M. Macdonald
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Simon Arridge
- University College London, Department of Computer Science, London, United Kingdom
| | - Samuel Powell
- University of Nottingham, Faculty of Engineering, Nottingham, United Kingdom
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Bench C, Hauptmann A, Cox B. Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:jbo-200119R. [PMID: 32840068 PMCID: PMC7443711 DOI: 10.1117/1.jbo.25.8.085003] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 07/23/2020] [Indexed: 05/02/2023]
Abstract
SIGNIFICANCE Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO2 from 2-D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as they are limited by the 2-D nature of the training data when the problem is inherently three-dimensional (3-D), and they have not been tested with realistic images. AIM To demonstrate the capability of deep neural networks to process whole 3-D images and output 3-D maps of vascular sO2 from realistic tissue models/images. APPROACH Two separate fully convolutional neural networks were trained to produce 3-D maps of vascular blood oxygen saturation and vessel positions from multiwavelength simulated images of tissue models. RESULTS The mean of the absolute difference between the true mean vessel sO2 and the network output for 40 examples was 4.4% and the standard deviation was 4.5%. CONCLUSIONS 3-D fully convolutional networks were shown capable of producing accurate sO2 maps using the full extent of spatial information contained within 3-D images generated under conditions mimicking real imaging scenarios. We demonstrate that networks can cope with some of the confounding effects present in real images such as limited-view artifacts and have the potential to produce accurate estimates in vivo.
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Affiliation(s)
- Ciaran Bench
- University College London, Department of Medical Physics and Biomedical Engineering, Gower Street, London, United Kingdom
- Address all correspondence to Ciaran Bench, E-mail:
| | - Andreas Hauptmann
- University of Oulu, Research Unit of Mathematical Sciences, Oulu, Finland
- University College London, Department of Computer Science, Gower Street, London, United Kingdom
| | - Ben Cox
- University College London, Department of Medical Physics and Biomedical Engineering, Gower Street, London, United Kingdom
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Pandey PK, Bharadwaj J, Naik N, Aggrawal HO. One-step fluorescence photoacoustic tomography with the optical radiative transfer model. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2020; 37:1175-1192. [PMID: 32609678 DOI: 10.1364/josaa.389476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 05/13/2020] [Indexed: 06/11/2023]
Abstract
We present adjoint-based Jacobian as well as gradient evaluations and corresponding reconstruction schemes to solve the fully nonlinear, optical radiative transfer modeled one-step fluorescence photoacoustic tomographic (FPAT) problem, which aims to reconstruct the map of absorption coefficient of the exogenous fluorophore from boundary photoacoustic data. The radiative transport equation (RTE) and frequency-domain photoacoustic equation have been employed to model light and photoacoustic wave propagation, respectively. Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno reconstruction schemes have been used corresponding to the evaluated Jacobians and gradients, respectively. Numerical reconstructions obtained from the two schemes have been validated for scattering-dominant as well as nonscattering-dominant media in 2D. To the best of our knowledge, these are the first one-step FPAT reconstruction results in literature based on the optical RTE model.
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Pandey PK, Gottam O, Naik N, Pradhan A. Gradient-based one-step fluorescence photoacoustic tomography. APPLIED OPTICS 2020; 59:4357-4366. [PMID: 32400412 DOI: 10.1364/ao.382879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 04/11/2020] [Indexed: 06/11/2023]
Abstract
We propose a gradient-based scheme to solve the fluorescence photoacoustic tomographic (FPAT) problem in a fully nonlinear one-step setting, which aims to reconstruct the map of the absorption coefficient of an exogenous fluorophore from boundary photoacoustic pressure data. Adjoint-based gradient evaluation is presented for the FPAT problem in a frequency-domain photoacoustic equation setting. Numerical validations of the resulting Broyden-Fletcher-Goldfarb-Shanno (BFGS) reconstruction scheme are carried out in two dimensions for full- as well as limited-data test cases, and the results are compared with existing Jacobian-based one-step FPAT reconstructions. The reasonably comparable results of the one-step gradient- and Jacobian-based FPAT reconstruction schemes, coupled with the significant computational savings of the former, potentially set up the one-step gradient-based schemes as an advantageous method of choice for FPAT reconstructions. Further reconstruction studies carried out using quantitative photoacoustic tomography (QPAT)-based chromophore reconstructions as inputs to the FPAT inversions show a robustness of fluorophore absorption coefficient reconstructions to the QPAT-obtained inputs.
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Ulrich L, Held KG, Jaeger M, Frenz M, Akarçay HG. Reliability assessment for blood oxygen saturation levels measured with optoacoustic imaging. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-15. [PMID: 32323509 PMCID: PMC7175414 DOI: 10.1117/1.jbo.25.4.046005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 03/25/2020] [Indexed: 06/11/2023]
Abstract
SIGNIFICANCE Quantitative optoacoustic (OA) imaging has the potential to provide blood oxygen saturation (SO2) estimates due to the proportionality between the measured signal and the blood's absorption coefficient. However, due to the wavelength-dependent attenuation of light in tissue, a spectral correction of the OA signals is required, and a prime challenge is the validation of both the optical characterization of the tissue and the SO2. AIM We propose to assess the reliability of SO2 levels retrieved from spectral fitting by measuring the similarity of OA spectra to the fitted blood absorption spectra. APPROACH We introduce a metric that quantifies the trends of blood spectra by assigning a pair of spectral slopes to each spectrum. The applicability of the metric is illustrated with in vivo measurements on a human forearm. RESULTS We show that physiologically sound SO2 values do not necessarily imply a successful spectral correction and demonstrate how the metric can be used to distinguish SO2 values that are trustworthy from unreliable ones. CONCLUSIONS The metric is independent of the methods used for the OA data acquisition, image reconstruction, and spectral correction, thus it can be readily combined with existing approaches, in order to monitor the accuracy of quantitative OA imaging.
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Affiliation(s)
- Leonie Ulrich
- University of Bern, Institute of Applied Physics, Biomedical Photonics, Bern, Switzerland
| | - Kai Gerrit Held
- University of Bern, Institute of Applied Physics, Biomedical Photonics, Bern, Switzerland
- ABB Switzerland, Corporate Research, Baden-Daettwil, Switzerland
| | - Michael Jaeger
- University of Bern, Institute of Applied Physics, Biomedical Photonics, Bern, Switzerland
| | - Martin Frenz
- University of Bern, Institute of Applied Physics, Biomedical Photonics, Bern, Switzerland
| | - Hidayet Günhan Akarçay
- University of Bern, Institute of Applied Physics, Biomedical Photonics, Bern, Switzerland
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Buchmann J, Kaplan B, Powell S, Prohaska S, Laufer J. Quantitative PA tomography of high resolution 3-D images: Experimental validation in a tissue phantom. PHOTOACOUSTICS 2020; 17:100157. [PMID: 31956487 PMCID: PMC6961715 DOI: 10.1016/j.pacs.2019.100157] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 11/29/2019] [Accepted: 12/05/2019] [Indexed: 05/18/2023]
Abstract
Quantitative photoacoustic tomography aims to recover the spatial distribution of absolute chromophore concentrations and their ratios from deep tissue, high-resolution images. In this study, a model-based inversion scheme based on a Monte-Carlo light transport model is experimentally validated on 3-D multispectral images of a tissue phantom acquired using an all-optical scanner with a planar detection geometry. A calibrated absorber allowed scaling of the measured data during the inversion, while an acoustic correction method was employed to compensate the effects of limited view detection. Chromophore- and fluence-dependent step sizes and Adam optimization were implemented to achieve rapid convergence. High resolution 3-D maps of absolute concentrations and their ratios were recovered with high accuracy. Potential applications of this method include quantitative functional and molecular photoacoustic tomography of deep tissue in preclinical and clinical studies.
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Affiliation(s)
- Jens Buchmann
- Institut für Physik, Martin-Luther-Universität Halle-Wittenberg, von-Danckelmann-Platz 3, 06120 Halle (Saale), Germany
- Institut für Optik und Atomare Physik, Technische Universität Berlin, Straße des 17, Juni 135, 10623 Berlin, Germany
| | - Bernhard Kaplan
- Visual Data Analysis, Zuse Institute Berlin, Takustr. 7, 14195 Berlin, Germany
| | - Samuel Powell
- Optics and Photonics Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Steffen Prohaska
- Visual Data Analysis, Zuse Institute Berlin, Takustr. 7, 14195 Berlin, Germany
| | - Jan Laufer
- Institut für Physik, Martin-Luther-Universität Halle-Wittenberg, von-Danckelmann-Platz 3, 06120 Halle (Saale), Germany
- Corresponding author.
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