Modeling combined ultrasound and photoacoustic imaging: Simulations aiding device development and artificial intelligence

Beard, 2011, Biomedical photoacoustic imaging, Interface Focus, 10.1098/rsfs.2011.0028 Tzoumas, 2016, Eigenspectra optoacoustic tomography achieves quantitative blood oxygenation imaging deep in tissues, Nat. Comm., 7, 10.1038/ncomms12121 Luke, 2012, Biomedical applications of photoacoustic imaging with exogenous contrast agents, Annal. of Biom. Eng., 40, 422, 10.1007/s10439-011-0449-4 Kolkman, 2008, Real-time in vivo photoacoustic and ultrasound imaging, Jour. of Biom. Opt., 13.5 Kim, 2020, Clinical Photoacoustic/Ultrasound imaging: systems and applications, In Clin. and Trans. Biophot, 10.1364/TRANSLATIONAL.2020.TM3B.5 Steinberg, 2019, Photoacoustic clinical imaging, Photoacoustics, 14, 77, 10.1016/j.pacs.2019.05.001 Wiacek, 2021, Photoacoustic-guided surgery from head to toe, Biomed. Opt. Express, 12, 2079, 10.1364/BOE.417984 Heijblom, 2012, Visualizing breast cancer using the Twente photoacoustic mammoscope: what do we learn from twelve new patient measurements?, Opt. Expr., 20, 11582, 10.1364/OE.20.011582 Ermilov, 2009, Laser optoacoustic imaging system for detection of breast cancer, Jr. of Biom. Opt., 14, 024007, 10.1117/1.3086616 Lin, 2018, Single-breath-hold photoacoustic computed tomography of the breast, Nat. Comm., 9, 1, 10.1038/s41467-018-04576-z Kothapalli, 2019, Simultaneous transrectal ultrasound and photoacoustic human prostate imaging, Sci. Transl. Med., 11, 10.1126/scitranslmed.aav2169 Salehi, 2016, Coregistered photoacoustic and ultrasound imaging and classification of ovarian cancer: ex vivo and in vivo studies, Jour. of Biom. Opt., 21 Regensburger, 2019, Detection of collagens by multispectral optoacoustic tomography as an imaging biomarker for Duchenne muscular dystrophy, Nat. Med., 25, 1905, 10.1038/s41591-019-0669-y Galanzha, 2019, In vivo liquid biopsy using Cytophone platform for photoacoustic detection of circulating tumor cells in patients with melanoma, Sci. Transl. Med., 11, 10.1126/scitranslmed.aat5857 Jo, 2017, A functional study of human inflammatory arthritis using photoacoustic imaging, Scien. Rep., 7, 1 Dima, 2016, In-vivo handheld optoacoustic tomography of the human thyroid, Photoacoustics, 4, 65, 10.1016/j.pacs.2016.05.003 Knieling, 2017, Multispectral optoacoustic tomography for assessment of Crohn’s disease activity, New England J. Med., 376, 1292, 10.1056/NEJMc1612455 Agrawal, 2021, Photoacoustic imaging of human vasculature using LED versus laser illumination: a comparison study on tissue phantoms and in vivo humans, Sensors, 21, 424, 10.3390/s21020424 Maslov, 2007, Effects of wavelength-dependent fluence attenuation on the noninvasive photoacoustic imaging of hemoglobin oxygen saturation in subcutaneous vasculature in vivo, Inverse Probl., 23, S113, 10.1088/0266-5611/23/6/S09 Treeby, 2013, Acoustic attenuation compensation in photoacoustic tomography using time-variant filtering, Jour. of Biom. Opt., 18, 036008, 10.1117/1.JBO.18.3.036008 Cox, 2012, Quantitative spectroscopic photoacoustic imaging: a review, Jour. of Biom. Opt., 17, 061202, 10.1117/1.JBO.17.6.061202 Pattyn, 2021, Model-based optical and acoustical compensation for photoacoustic tomography of heterogeneous mediums, Photoacoustics, 100275, 10.1016/j.pacs.2021.100275 Huang, 2013, Full-wave iterative image reconstruction in photoacoustic tomography with acoustically inhomogeneous media, IEEE Trans. Med. Imaging, 32, 1097, 10.1109/TMI.2013.2254496 Cox, 2009, Artifact trapping during time reversal photoacoustic imaging for acoustically heterogeneous media, IEEE Tr. On Med. Imag., 29, 387, 10.1109/TMI.2009.2032358 Singh, 2015, Photoacoustic-guided focused ultrasound (PAFUSion) for identifying reflection artifacts in photoacoustic imaging, Photoacoustics, 3, 123, 10.1016/j.pacs.2015.09.001 Agrawal, 2020, Design, development, and multi-characterization of an integrated clinical transrectal ultrasound and photoacoustic device for human prostate imaging, Diagnostics, 10, 566, 10.3390/diagnostics10080566 Dangi, 2019, Lithium niobate-based transparent ultrasound transducers for photoacoustic imaging, Opt. Lett., 44, 5326, 10.1364/OL.44.005326 Nyayapathi, 2019, Dual scan mammoscope (DSM)—a new portable photoacoustic breast imaging system with scanning in craniocaudal plane, IEEE Trans. Inf. Technol. Biomed. Agrawal, 2019, Light-emitting-Diode-Based multispectral photoacoustic computed tomography system, Sensors, 19, 4861, 10.3390/s19224861 Huang, 2013, Full-wave iterative image reconstruction in photoacoustic tomography with acoustically inhomogeneous media, IEEE Tr. on Med. Imag., 32, 1097, 10.1109/TMI.2013.2254496 Shamekhi, 2020, Eigenspace-based minimum variance beamformer combined with sign coherence factor: application to linear-array photoacoustic imaging, Ultrasonics, 108, 106174, 10.1016/j.ultras.2020.106174 Olefir, 2020, Deep learning-based spectral unmixing for optoacoustic imaging of tissue oxygen saturation, IEEE Tr. on Med. Imag., 39, 3643, 10.1109/TMI.2020.3001750 Allman, 2018, Photoacoustic source detection and reflection artifact removal enabled by deep learning, IEEE Tr. on Med. Imag., 37, 1464, 10.1109/TMI.2018.2829662 Hauptmann, 2020, Deep learning in photoacoustic tomography: current approaches and future directions, J. Biomed. Opt., 25, 112903, 10.1117/1.JBO.25.11.112903 Deng, 2021, Deep learning in photoacoustic imaging: a review, J. Biomed. Opt., 26, 040901, 10.1117/1.JBO.26.4.040901 Zhen, 2007, Three‐dimensional finite‐element‐based photoacoustic tomography: Reconstruction algorithm and simulations, Med. Phy., 34, 538, 10.1118/1.2409234 Saha, 2011, A simulation study on photoacoustic signals from red blood cells, J. Acoust. Soc. Am., 129, 2935, 10.1121/1.3570946 Mastanduno, 2016, Quantitative photoacoustic image reconstruction improves accuracy in deep tissue structures, Biomed. Opt. Express, 7, 3811, 10.1364/BOE.7.003811 Akhlaghi, 2019, Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction, Jr. of Biom. Opt., 24, 121910 Jacques, 2014, Coupling 3D Monte Carlo light transport in optically heterogeneous tissues to photoacoustic signal generation, Photoacoustics, 2, 137, 10.1016/j.pacs.2014.09.001 Treeby, 2010, k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields, Jr. of Biom. Opt., 15, 021314, 10.1117/1.3360308 Rejesh, 2013, Deconvolution-based deblurring of reconstructed images in photoacoustic/thermoacoustic tomography, JOSA A, 30, 1994, 10.1364/JOSAA.30.001994 Wang, 1993, Hybrid model of Monte Carlo simulation and diffusion theory for light reflectance by turbid media, JOSA A, 10, 1746, 10.1364/JOSAA.10.001746 Dehghani, 2009, Near infrared optical tomography using NIRFAST: algorithm for numerical model and image reconstruction, Int. Jr. for Numer. Meth. in Biomed. Eng., 25, 711 Agrawal, 2019, Optimal design of combined ultrasound and multispectral photoacoustic deep tissue imaging devices using hybrid simulation platform, 10878, 108782L Jacques, 2013, Optical properties of biological tissues: a review, Phys. Med., 58, R37 OMLC website, http://omlc.org/spectra/index.html. Luke, 2013, Optical wavelength selection for improved spectroscopic photoacoustic imaging, Photoacoustics, 1, 36, 10.1016/j.pacs.2013.08.001 Shung, 1976, Scattering of ultrasound by blood, IEEE Trans. Biomed. Eng., 6, 460, 10.1109/TBME.1976.324604 Yao, 2014, Photoacoustic measurement of the Grüneisen parameter of tissue, Jr. of Biom. Opt., 19, 017007, 10.1117/1.JBO.19.1.017007 Kruger, 1995, Photoacoustic ultrasound (PAUS)—reconstruction tomography, Med. Phys., 22, 1605, 10.1118/1.597429 Lawson, 1974, Solving least-squares problems, 161 ITIS foundation website: https://itis.swiss/virtual-population/tissue-properties/overview/. Mcintosh, 2010, A comprehensive tissue properties database provided for the thermal assessment of a human at rest, Biophy. Rev. and Lett., 5.03, 129, 10.1142/S1793048010001184 Daoudi, 2014, Handheld probe integrating laser diode and ultrasound transducer array for ultrasound/photoacoustic dual modality imaging, Opt. Express, 22, 26365, 10.1364/OE.22.026365 https://www.acrdsi.org/DSI-Services/FDA-Cleared-AI-Algorithms. Mikołajczyk, 2018, Data augmentation for improving deep learning in image classification problem, 117 Davoudi, 2019, Deep learning optoacoustic tomography with sparse data, Int. J. Mach. Intell. Sens. Signal Process., 1, 453 Anas, 2018, Enabling fast and high quality LED photoacoustic imaging: a recurrent neural networks based approach, Biom. Opt. Expr., 9, 3852, 10.1364/BOE.9.003852 Farnia, 2020, Dictionary learning technique enhances signal in LED-based photoacoustic imaging, Biom.l Opt. Exp., 11, 2533, 10.1364/BOE.387364 Hariri, 2020, Deep learning improves contrast in low-fluence photoacoustic imaging, Biomed. Opt. Express, 11, 3360, 10.1364/BOE.395683 Johnstonbaugh, 2020, A deep learning approach to photoacoustic wavefront localization in deep-tissue medium, IEEE Tr. on Ultras. Ferro. and Freq. Contr., 10.1109/TUFFC.2020.2964698 Agrawal, 2021, Learning optical scattering through symmetrical orthogonality enforced independent components for unmixing deep tissue photoacoustic signals, Ieee Sens. Lett., 5, 1, 10.1109/LSENS.2021.3073927 Agrawal, 2021, In vivo demonstration of reflection artifact reduction in LED-based photoacoustic imaging using deep learning, 11642, 116421K