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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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2
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Park S, Villa U, Li F, Cam RM, Oraevsky AA, Anastasio MA. Stochastic three-dimensional numerical phantoms to enable computational studies in quantitative optoacoustic computed tomography of breast cancer. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:066002. [PMID: 37347003 PMCID: PMC10281048 DOI: 10.1117/1.jbo.28.6.066002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 05/18/2023] [Accepted: 05/22/2023] [Indexed: 06/23/2023]
Abstract
Significance When developing a new quantitative optoacoustic computed tomography (OAT) system for diagnostic imaging of breast cancer, objective assessments of various system designs through human trials are infeasible due to cost and ethical concerns. In prototype stages, however, different system designs can be cost-efficiently assessed via virtual imaging trials (VITs) employing ensembles of digital breast phantoms, i.e., numerical breast phantoms (NBPs), that convey clinically relevant variability in anatomy and optoacoustic tissue properties. Aim The aim is to develop a framework for generating ensembles of realistic three-dimensional (3D) anatomical, functional, optical, and acoustic NBPs and numerical lesion phantoms (NLPs) for use in VITs of OAT applications in the diagnostic imaging of breast cancer. Approach The generation of the anatomical NBPs was accomplished by extending existing NBPs developed by the U.S. Food and Drug Administration. As these were designed for use in mammography applications, substantial modifications were made to improve blood vasculature modeling for use in OAT. The NLPs were modeled to include viable tumor cells only or a combination of viable tumor cells, necrotic core, and peripheral angiogenesis region. Realistic optoacoustic tissue properties were stochastically assigned in the NBPs and NLPs. Results To advance optoacoustic and optical imaging research, 84 datasets have been released; these consist of anatomical, functional, optical, and acoustic NBPs and the corresponding simulated multi-wavelength optical fluence, initial pressure, and OAT measurements. The generated NBPs were compared with clinical data with respect to the volume of breast blood vessels and spatially averaged effective optical attenuation. The usefulness of the proposed framework was demonstrated through a case study to investigate the impact of acoustic heterogeneity on OAT images of the breast. Conclusions The proposed framework will enhance the authenticity of virtual OAT studies and can be widely employed for the investigation and development of advanced image reconstruction and machine learning-based methods, as well as the objective evaluation and optimization of the OAT system designs.
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Affiliation(s)
- Seonyeong Park
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
| | - Umberto Villa
- The University of Texas at Austin, Oden Institute for Computational Engineering and Sciences, Austin, Texas, United States
| | - Fu Li
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
| | - Refik Mert Cam
- University of Illinois Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
| | | | - Mark A. Anastasio
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
- University of Illinois Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
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Omidali M, Mardanshahi A, Särestöniemi M, Zhao Z, Myllylä T. Acousto-Optics: Recent Studies and Medical Applications. BIOSENSORS 2023; 13:bios13020186. [PMID: 36831952 PMCID: PMC9953934 DOI: 10.3390/bios13020186] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/16/2023] [Accepted: 01/20/2023] [Indexed: 05/31/2023]
Abstract
Development of acousto-optic (AO) techniques has made progress in recent years across a range of medical application fields, especially in improving resolution, detection speed, and imaging depth. This paper presents a comprehensive overview of recent advancements in AO-based techniques that have been presented after the previously published review in 2017. The survey covers a description of theoretical modeling strategies and numerical simulation methods as well as recent applications in medical fields. It also provides a comparison between different techniques in terms of complexity, achieved depth in tissue, and resolution. In addition, a comparison between different numerical simulation methods will be outlined. Additionally, a number of challenges faced by AO techniques are considered, particularly in the context of realistic in vivo imaging. Finally, the paper discusses prospects of AO-based medical diagnosis methods.
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Affiliation(s)
- Mohammadreza Omidali
- Optoelectronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, 90570 Oulu, Finland
| | - Ali Mardanshahi
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, 90220 Oulu, Finland
| | - Mariella Särestöniemi
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, 90220 Oulu, Finland
- Center for Wireless Communications, University of Oulu, 90570 Oulu, Finland
| | - Zuomin Zhao
- Optoelectronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, 90570 Oulu, Finland
| | - Teemu Myllylä
- Optoelectronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, 90570 Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, 90220 Oulu, Finland
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4
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Madasamy A, Gujrati V, Ntziachristos V, Prakash J. Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:106004. [PMID: 36209354 PMCID: PMC9547608 DOI: 10.1117/1.jbo.27.10.106004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 08/30/2022] [Indexed: 06/16/2023]
Abstract
SIGNIFICANCE Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect. AIM Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium. APPROACH Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets. RESULTS The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction. CONCLUSIONS The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.
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Affiliation(s)
- Arumugaraj Madasamy
- Indian Institute of Science, Department of Instrumentation and Applied Physics, Bengaluru, Karnataka, India
| | - Vipul Gujrati
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München (GmbH), Neuherberg, Germany
- Technical University of Munich, School of Medicine, Chair of Biological Imaging, Munich, Germany
| | - Vasilis Ntziachristos
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München (GmbH), Neuherberg, Germany
- Technical University of Munich, School of Medicine, Chair of Biological Imaging, Munich, Germany
- Technical University of Munich, Munich Institute of Robotics and Machine Intelligence (MIRMI), Munich, Germany
| | - Jaya Prakash
- Indian Institute of Science, Department of Instrumentation and Applied Physics, Bengaluru, Karnataka, India
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5
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Muller JW, Arabul MÜ, Schwab HM, Rutten MCM, van Sambeek MRHM, Wu M, Lopata RGP. Modeling toolchain for realistic simulation of photoacoustic data acquisition. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:096005. [PMID: 36104838 PMCID: PMC9470848 DOI: 10.1117/1.jbo.27.9.096005] [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: 06/07/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
SIGNIFICANCE Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking. AIM A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation. APPROACH Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood. Ex vivo human plaque samples were simulated to validate the methods in more complex tissues. RESULTS The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately. CONCLUSIONS A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.
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Affiliation(s)
- Jan-Willem Muller
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
- Catharina Hospital, Department of Vascular Surgery, Eindhoven, The Netherlands
| | - Mustafa Ü. Arabul
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
| | - Hans-Martin Schwab
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
| | - Marcel C. M. Rutten
- Cardiovascular Biomechanics Group, Department of Biomedical Engineering, Eindhoven, The Netherlands
| | - Marc R. H. M. van Sambeek
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
- Catharina Hospital, Department of Vascular Surgery, Eindhoven, The Netherlands
| | - Min Wu
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
| | - Richard G. P. Lopata
- Eindhoven University of Technology, Photoacoustics and Ultrasound Laboratory Eindhoven, Department of Biomedical Engineering, Eindhoven, The Netherlands
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Gröhl J, Dreher KK, Schellenberg M, Rix T, Holzwarth N, Vieten P, Ayala L, Bohndiek SE, Seitel A, Maier-Hein L. SIMPA: an open-source toolkit for simulation and image processing for photonics and acoustics. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210395SSR. [PMID: 35380031 PMCID: PMC8978263 DOI: 10.1117/1.jbo.27.8.083010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/28/2022] [Indexed: 05/09/2023]
Abstract
SIGNIFICANCE Optical and acoustic imaging techniques enable noninvasive visualisation of structural and functional properties of tissue. The quantification of measurements, however, remains challenging due to the inverse problems that must be solved. Emerging data-driven approaches are promising, but they rely heavily on the presence of high-quality simulations across a range of wavelengths due to the lack of ground truth knowledge of tissue acoustical and optical properties in realistic settings. AIM To facilitate this process, we present the open-source simulation and image processing for photonics and acoustics (SIMPA) Python toolkit. SIMPA is being developed according to modern software design standards. APPROACH SIMPA enables the use of computational forward models, data processing algorithms, and digital device twins to simulate realistic images within a single pipeline. SIMPA's module implementations can be seamlessly exchanged as SIMPA abstracts from the concrete implementation of each forward model and builds the simulation pipeline in a modular fashion. Furthermore, SIMPA provides comprehensive libraries of biological structures, such as vessels, as well as optical and acoustic properties and other functionalities for the generation of realistic tissue models. RESULTS To showcase the capabilities of SIMPA, we show examples in the context of photoacoustic imaging: the diversity of creatable tissue models, the customisability of a simulation pipeline, and the degree of realism of the simulations. CONCLUSIONS SIMPA is an open-source toolkit that can be used to simulate optical and acoustic imaging modalities. The code is available at: https://github.com/IMSY-DKFZ/simpa, and all of the examples and experiments in this paper can be reproduced using the code available at: https://github.com/IMSY-DKFZ/simpa_paper_experiments.
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Affiliation(s)
- Janek Gröhl
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Kris K. Dreher
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Physics and Astronomy, Heidelberg, Germany
| | - Melanie Schellenberg
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
- HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg, Germany
| | - Tom Rix
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
| | - Niklas Holzwarth
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Patricia Vieten
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Physics and Astronomy, Heidelberg, Germany
| | - Leonardo Ayala
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Medical Faculty, Heidelberg, Germany
| | - Sarah E. Bohndiek
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, United Kingdom
- University of Cambridge, Department of Physics, Cambridge, United Kingdom
| | - Alexander Seitel
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Lena Maier-Hein
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
- Heidelberg University, Medical Faculty, Heidelberg, Germany
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7
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Bao Y, Deng H, Wang X, Zuo H, Ma C. Development of a digital breast phantom for photoacoustic computed tomography. BIOMEDICAL OPTICS EXPRESS 2021; 12:1391-1406. [PMID: 33796361 PMCID: PMC7984796 DOI: 10.1364/boe.416406] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/16/2021] [Accepted: 01/26/2021] [Indexed: 05/18/2023]
Abstract
Photoacoustic (PA) imaging provides morphological and functional information about angiogenesis and thus is potentially suitable for breast cancer diagnosis. However, the development of PA breast imaging has been hindered by inadequate patients and a lack of ground truth images. Here, we report a digital breast phantom with realistic acoustic and optical properties, with which a digital PA-ultrasound imaging pipeline is developed to create a diverse pool of virtual patients with three types of masses: ductal carcinoma in situ, invasive breast cancer, and fibroadenoma. The experimental results demonstrate that our model is realistic, flexible, and can be potentially useful for accelerating the development of PA breast imaging technology.
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Affiliation(s)
- Youwei Bao
- The Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
| | - Handi Deng
- The Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
| | - Xuanhao Wang
- The Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
| | - Hongzhi Zuo
- The Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
| | - Cheng Ma
- The Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China
- Beijing Innovation Center for Future Chip, Beijing, 100084, China
- Corresponding author:
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8
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Agrawal S, Fadden C, Dangi A, Yang X, Albahrani H, Frings N, Heidari Zadi S, Kothapalli SR. Light-Emitting-Diode-Based Multispectral Photoacoustic Computed Tomography System. SENSORS 2019; 19:s19224861. [PMID: 31717260 PMCID: PMC6891584 DOI: 10.3390/s19224861] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 11/02/2019] [Accepted: 11/06/2019] [Indexed: 12/16/2022]
Abstract
Photoacoustic computed tomography (PACT) has been widely explored for non-ionizing functional and molecular imaging of humans and small animals. In order for light to penetrate deep inside tissue, a bulky and high-cost tunable laser is typically used. Light-emitting diodes (LEDs) have recently emerged as cost-effective and portable alternative illumination sources for photoacoustic imaging. In this study, we have developed a portable, low-cost, five-dimensional (x, y, z, t, λ ) PACT system using multi-wavelength LED excitation to enable similar functional and molecular imaging capabilities as standard tunable lasers. Four LED arrays and a linear ultrasound transducer detector array are housed in a hollow cylindrical geometry that rotates 360 degrees to allow multiple projections through the subject of interest placed inside the cylinder. The structural, functional, and molecular imaging capabilities of the LED-PACT system are validated using various tissue-mimicking phantom studies. The axial, lateral, and elevational resolutions of the system at 2.3 cm depth are estimated as 0.12 mm, 0.3 mm, and 2.1 mm, respectively. Spectrally unmixed photoacoustic contrasts from tubes filled with oxy- and deoxy-hemoglobin, indocyanine green, methylene blue, and melanin molecules demonstrate the multispectral molecular imaging capabilities of the system. Human-finger-mimicking phantoms made of a bone and blood tubes show structural and functional oxygen saturation imaging capabilities. Together, these results demonstrate the potential of the proposed LED-based, low-cost, portable PACT system for pre-clinical and clinical applications.
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Affiliation(s)
- Sumit Agrawal
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Christopher Fadden
- Department of Electrical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA;
| | - Ajay Dangi
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Xinyi Yang
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Hussain Albahrani
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Neilesh Frings
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Sara Heidari Zadi
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA; (S.A.); (A.D.); (X.Y.); (H.A.); (N.F.); (S.H.Z.)
- Penn State Cancer Institute, Pennsylvania State University, Hershey, PA 17033, USA
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, PA 16802, USA
- Correspondence:
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9
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Akhlaghi N, Pfefer TJ, Wear KA, Garra BS, Vogt WC. Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-12. [PMID: 31705636 PMCID: PMC7005568 DOI: 10.1117/1.jbo.24.12.121910] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 10/14/2019] [Indexed: 05/05/2023]
Abstract
As photoacoustic imaging (PAI) technology matures, computational modeling will increasingly represent a critical tool for facilitating clinical translation through predictive simulation of real-world performance under a wide range of device and biological conditions. While modeling currently offers a rapid, inexpensive tool for device development and prediction of fundamental image quality metrics (e.g., spatial resolution and contrast ratio), rigorous verification and validation will be required of models used to provide regulatory-grade data that effectively complements and/or replaces in vivo testing. To address methods for establishing model credibility, we developed an integrated computational model of PAI by coupling a previously developed three-dimensional Monte Carlo model of tissue light transport with a two-dimensional (2D) acoustic wave propagation model implemented in the well-known k-Wave toolbox. We then evaluated ability of the model to predict basic image quality metrics by applying standardized verification and validation principles for computational models. The model was verified against published simulation data and validated against phantom experiments using a custom PAI system. Furthermore, we used the model to conduct a parametric study of optical and acoustic design parameters. Results suggest that computationally economical 2D acoustic models can adequately predict spatial resolution, but metrics such as signal-to-noise ratio and penetration depth were difficult to replicate due to challenges in modeling strong clutter observed in experimental images. Parametric studies provided quantitative insight into complex relationships between transducer characteristics and image quality as well as optimal selection of optical beam geometry to ensure adequate image uniformity. Multidomain PAI simulation tools provide high-quality tools to aid device development and prediction of real-world performance, but further work is needed to improve model fidelity, especially in reproducing image noise and clutter.
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Affiliation(s)
- Nima Akhlaghi
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States
- Address all correspondence to Nima Akhlaghi, E-mail:
| | - T. Joshua Pfefer
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States
| | - Keith A. Wear
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States
| | - Brian S. Garra
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States
| | - William C. Vogt
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, United States
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