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  • Review Article
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Clinical translation of photoacoustic imaging

Nature Reviews Bioengineering volume 3, pages 193–212 (2025)Cite this article

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Abstract

Photoacoustic imaging (PAI), also known as optoacoustic imaging, is a promising biomedical imaging technique that combines the benefits of rich optical contrast and high ultrasonic spatial resolution to overcome the limited penetration depth of light in living subjects. Basic biomedical research conducted with PAI in preclinical studies has generated much interest and shown outstanding potential for clinical and commercial translation. PAI has captured morphological, functional and molecular information in studies of living animals and humans, providing intrinsic clinical indicators from early diagnosis through to treatment monitoring. This Review presents the fundamentals of PAI technology and various clinical PAI systems and addresses key findings from pilot and clinical patient studies of human organ systems. The Review also discusses technical and non-technical challenges in clinical scenarios, emphasizes the importance of standardization in accelerating clinical translation, and summarizes the current state of the PAI regulatory process.

Key points

  • By combining optics and ultrasound, photoacoustic imaging breaks the fundamental penetration depth barrier of traditional optical imaging, providing absorption-based rich optical contrast and high ultrasonic spatial resolution in living tissues.

  • Photoacoustic imaging systems are implemented in various forms to suit diagnostic purposes in clinical settings: dual-modal photoacoustic and ultrasound imaging based on conventional ultrasound imaging systems, station-based tomographic photoacoustic imaging, and mesoscopic/microscopic photoacoustic imaging.

  • Photoacoustic pilot and clinical studies of human functional systems have demonstrated high potential for translating the modality into clinical practice.

  • Despite the notable outcomes of photoacoustic imaging, several challenges remain: overcoming technical and non-technical limitations, standardizing image analyses, obtaining regulatory approval, and securing medical insurance coverage for its commercialization.

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Fig. 1: Overview of PAI.
Fig. 2: Various clinical PAI system configurations.
Fig. 3: Representative clinical photoacoustic imaging results for human functional systems.

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References

  1. Park, Y., Depeursinge, C. & Popescu, G. Quantitative phase imaging in biomedicine. Nat. Photonics 12, 578–589 (2018).

    MATH  Google Scholar 

  2. Ntziachristos, V. Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods 7, 603–614 (2010).

    MATH  Google Scholar 

  3. Yang, S.-T. et al. Carbon dots for optical imaging in vivo. J. Am. Chem. Soc. 131, 11308–11309 (2009).

    MATH  Google Scholar 

  4. Scholkmann, F. et al. A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage 85, 6–27 (2014).

    MATH  Google Scholar 

  5. Geslien, G. E., Fisher, J. R. & DeLaney, C. Transillumination in breast cancer detection: screening failures and potential. AJR Am. J. Roentgenol. 144, 619–622 (1985).

    MATH  Google Scholar 

  6. Pichler, B. J., Wehrl, H. F., Kolb, A. & Judenhofer, M. S. Positron emission tomography/magnetic resonance imaging: the next generation of multimodality imaging? Semin. Nucl. Med. 38, 199–208 (2008).

    MATH  Google Scholar 

  7. Leide-Svegborn, S. Radiation exposure of patients and personnel from a PET/CT procedure with 18F-FDG. Radiat. Prot. Dosimetry 139, 208–213 (2010).

    Google Scholar 

  8. Welch, J. N., Johnson, J. A., Bax, M. R., Badr, R. & Shahidi, R. In IEEE Ultrasonics Symposium Proceedings. An International Symposium (Cat. No. 00CH37121) 1601–1604 (IEEE, 2000).

  9. Beller, S. et al. Image-guided surgery of liver metastases by three-dimensional ultrasound-based optoelectronic navigation. J. Br. Surg. 94, 866–875 (2007).

    MATH  Google Scholar 

  10. Gill, R. W. Measurement of blood flow by ultrasound: accuracy and sources of error. Ultrasound Med. Biol. 11, 625–641 (1985).

    MATH  Google Scholar 

  11. Sigrist, R. M., Liau, J., El Kaffas, A., Chammas, M. C. & Willmann, J. K. Ultrasound elastography: review of techniques and clinical applications. Theranostics 7, 1303 (2017).

    Google Scholar 

  12. Zhang, P. et al. High-resolution deep functional imaging of the whole mouse brain by photoacoustic computed tomography in vivo. J. Biophotonics 11, e201700024 (2018).

    Google Scholar 

  13. Wang, L. V. & Hu, S. Photoacoustic tomography: in vivo imaging from organelles to organs. Science 335, 1458–1462 (2012).

    MATH  Google Scholar 

  14. Choi, W. et al. Recent advances in contrast-enhanced photoacoustic imaging: overcoming the physical and practical challenges. Chem. Rev. 123, 7379–7419 (2023).

    MATH  Google Scholar 

  15. Kim, J. et al. Programmable real-time clinical photoacoustic and ultrasound imaging system. Sci. Rep. 6, 35137 (2016).

    Google Scholar 

  16. Wen, Y. et al. Clinical photoacoustic/ultrasound dual-modal imaging: current status and future trends. Front. Physiol. 13, 2227 (2022).

    MATH  Google Scholar 

  17. Bell, A. G. The photophone. Science 1, 130–134 (1880).

    MATH  Google Scholar 

  18. Vengerov, M. An optical-acoustic method of gas analysis. Nature 158, 28–29 (1946).

    MATH  Google Scholar 

  19. Delany, M. E. The optic-acoustic effect in gases. Sci. Prog. 47, 459–467 (1959).

    MATH  Google Scholar 

  20. Rosencwaig, A. Photoacoustic spectroscopy of solids. Opt. Commun. 7, 305–308 (1973).

    MATH  Google Scholar 

  21. Busse, G. & Rosencwaig, A. Subsurface imaging with photoacoustics. Appl. Phys. Lett. 36, 815–816 (1980).

    MATH  Google Scholar 

  22. Wada, K. et al. Laser photoacoustic microscopy for the determination of dye on a solid biopolymer. Chem. Pharm. Bull. 33, 1316–1319 (1985).

    MATH  Google Scholar 

  23. Wada, K., Masujima, T., Yoshida, H. & Imai, H. Photoacoustic microscopy for the analysis of peroxidase activity in a biological tissue. Chem. Pharm. Bull. 34, 1834–1836 (1986).

    MATH  Google Scholar 

  24. Diebold, G., Sun, T. & Khan, M. Photoacoustic monopole radiation in one, two, and three dimensions. Phys. Rev. Lett. 67, 3384 (1991).

    MATH  Google Scholar 

  25. Oraevsky, A. A., Jacques, S. L., Esenaliev, R. O. & Tittel, F. K. In Laser-Tissue Interaction V; and Ultraviolet Radiation Hazards 122–128 (SPIE, 1994).

  26. Kruger, R. A. Photoacoustic ultrasound. Med. Phys. 21, 127–131 (1994).

    MATH  Google Scholar 

  27. Manohar, S. & Razansky, D. Photoacoustics: a historical review. Adv. Opt. Photonics 8, 586–617 (2016).

    MATH  Google Scholar 

  28. Savateeva, E. V. et al. In Biomedical Optoacoustics 55–66 (SPIE, 2000).

  29. Wang, X. et al. Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain. Nat. Biotechnol. 21, 803–806 (2003).

    MATH  Google Scholar 

  30. Oraevsky, A. A. et al. In Biomedical Optoacoustics II 6–15 (SPIE, 2001).

  31. Taruttis, A. & Ntziachristos, V. Advances in real-time multispectral optoacoustic imaging and its applications. Nat. Photonics 9, 219–227 (2015).

    MATH  Google Scholar 

  32. Park, B., Oh, D., Kim, J. & Kim, C. Functional photoacoustic imaging: from nano- and micro- to macro-scale. Nano Converg. 10, 29 (2023).

    MATH  Google Scholar 

  33. Park, B., Kim, C. & Kim, J. Recent advances in ultrasound and photoacoustic analysis for thyroid cancer diagnosis. Adv. Phys. Res. 2, 2200070 (2023).

    MATH  Google Scholar 

  34. Park, E.-Y., Lee, H., Han, S., Kim, C. & Kim, J. Photoacoustic imaging systems based on clinical ultrasound platform. Exp. Biol. Med. 247, 551–560 (2022).

    MATH  Google Scholar 

  35. Lee, C., Kim, C. & Park, B. Review of three-dimensional handheld photoacoustic and ultrasound imaging systems and their applications. Sensors 23, 8149 (2023).

    MATH  Google Scholar 

  36. Yang, J., Choi, S. & Kim, C. Practical review on photoacoustic computed tomography using curved ultrasound array transducer. Biomed. Eng. Lett. 12, 19–35 (2021).

    Google Scholar 

  37. Yang, J., Choi, S., Kim, J., Park, B. & Kim, C. Recent advances in deep-learning-enhanced photoacoustic imaging. Adv. Photonics Nexus 2, 054001 (2023).

    MATH  Google Scholar 

  38. Attia, A. B. E. et al. A review of clinical photoacoustic imaging: current and future trends. Photoacoustics 16, 100144 (2019).

    MATH  Google Scholar 

  39. Zhang, H. F., Maslov, K., Stoica, G. & Wang, L. V. Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging. Nat. Biotechnol. 24, 848–851 (2006).

    MATH  Google Scholar 

  40. Park, B. et al. 3D wide‐field multispectral photoacoustic imaging of human melanomas in vivo: a pilot study. J. Eur. Acad. Dermatol. Venereol. 35, 669–676 (2021).

    MATH  Google Scholar 

  41. Shi, J. et al. High-resolution, high-contrast mid-infrared imaging of fresh biological samples with ultraviolet-localized photoacoustic microscopy. Nat. Photonics 13, 609–615 (2019).

    MATH  Google Scholar 

  42. Baik, J. W. et al. Intraoperative label‐free photoacoustic histopathology of clinical specimens. Laser Photonics Rev. 15, 2100124 (2021).

    MATH  Google Scholar 

  43. Fasoula, N.-A. et al. Non-invasive multispectral optoacoustic tomography resolves intrahepatic lipids in patients with hepatic steatosis. Photoacoustics 29, 100454 (2023).

    MATH  Google Scholar 

  44. Regensburger, A. P. et al. Detection of collagens by multispectral optoacoustic tomography as an imaging biomarker for Duchenne muscular dystrophy. Nat. Med. 25, 1905–1915 (2019).

    MATH  Google Scholar 

  45. Weber, J., Beard, P. C. & Bohndiek, S. E. Contrast agents for molecular photoacoustic imaging. Nat. Methods 13, 639–650 (2016).

    MATH  Google Scholar 

  46. Yao, J. et al. High-speed label-free functional photoacoustic microscopy of mouse brain in action. Nat. Methods 12, 407–410 (2015).

    MATH  Google Scholar 

  47. Kim, J. et al. Multiparametric photoacoustic analysis of human thyroid cancers in vivophotoacoustic analysis of human thyroid cancers. Cancer Res. 81, 4849–4860 (2021).

    MATH  Google Scholar 

  48. Yao, J., Maslov, K. I., Shi, Y., Taber, L. A. & Wang, L. V. In vivo photoacoustic imaging of transverse blood flow by using Doppler broadening of bandwidth. Opt. Lett. 35, 1419–1421 (2010).

    MATH  Google Scholar 

  49. Singh, M. S. & Thomas, A. Photoacoustic elastography imaging: a review. J. Biomed. Opt. 24, 040902 (2019).

    MATH  Google Scholar 

  50. Yao, J. et al. Noninvasive photoacoustic computed tomography of mouse brain metabolism in vivo. Neuroimage 64, 257–266 (2013).

    MATH  Google Scholar 

  51. Kim, C., Song, K. H., Gao, F. & Wang, L. V. Sentinel lymph nodes and lymphatic vessels: noninvasive dual-modality in vivo mapping by using indocyanine green in rats — volumetric spectroscopic photoacoustic imaging and planar fluorescence imaging. Radiology 255, 442–450 (2010).

    Google Scholar 

  52. Cox, B. T. & Treeby, B. E. Artifact trapping during time reversal photoacoustic imaging for acoustically heterogeneous media. IEEE Trans. Med. Imaging 29, 387–396 (2009).

    MATH  Google Scholar 

  53. Jeon, S. et al. Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans. Photoacoustics 15, 100136 (2019).

    MATH  Google Scholar 

  54. Jeng, G.-S. et al. Real-time interleaved spectroscopic photoacoustic and ultrasound (PAUS) scanning with simultaneous fluence compensation and motion correction. Nat. Commun. 12, 716 (2021).

    MATH  Google Scholar 

  55. Puglisi, J. D. & Tinoco Jr, I. In Methods in Enzymology 180, 304–325 (Elsevier, 1989).

  56. Stoscheck, C. M. In Methods in Enzymology 182, 50–68 (Elsevier, 1990).

  57. Choi, S. et al. Deep learning enhances multiparametric dynamic volumetric photoacoustic computed tomography in vivo (DL‐PACT). Adv. Sci. 10, 2202089 (2023).

    Google Scholar 

  58. Lv, J., Xu, Y., Xu, L. & Nie, L. Quantitative functional evaluation of liver fibrosis in mice with dynamic contrast-enhanced photoacoustic imaging. Radiology 300, 89–97 (2021).

    MATH  Google Scholar 

  59. Suzuki, Y. et al. Subcutaneous lymphatic vessels in the lower extremities: comparison between photoacoustic lymphangiography and near-infrared fluorescence lymphangiography. Radiology 295, 469–474 (2020).

    MATH  Google Scholar 

  60. Paulus, L. P. et al. Contrast‐enhanced multispectral optoacoustic tomography for functional assessment of the gastrointestinal tract. Adv. Sci. 10, e2302562 (2023).

    MATH  Google Scholar 

  61. Feng, T. et al. Detection of collagen by multi-wavelength photoacoustic analysis as a biomarker for bone health assessment. Photoacoustics 24, 100296 (2021).

    Google Scholar 

  62. Nagae, K. et al. Real-time 3D photoacoustic visualization system with a wide field of view for imaging human limbs. F1000Res 7, 1813 (2018).

    MATH  Google Scholar 

  63. Lei, S. et al. In vivo three-dimensional multispectral photoacoustic imaging of dual enzyme-driven cyclic cascade reaction for tumor catalytic therapy. Nat. Commun. 13, 1298 (2022).

    MATH  Google Scholar 

  64. Paltauf, G., Nuster, R. & Frenz, M. Progress in biomedical photoacoustic imaging instrumentation toward clinical application. J. Appl. Phys. 128, 180907 (2020).

    MATH  Google Scholar 

  65. Oraevsky, A. et al. In Photons Plus Ultrasound: Imaging and Sensing 217–226 (SPIE, 2018).

  66. Neuschler, E. I. et al. A pivotal study of optoacoustic imaging to diagnose benign and malignant breast masses: a new evaluation tool for radiologists. Radiology 287, 398–412 (2017).

    MATH  Google Scholar 

  67. Taruttis, A. et al. Optoacoustic imaging of human vasculature: feasibility by using a handheld probe. Radiology 281, 256–263 (2016).

    MATH  Google Scholar 

  68. Knieling, F. et al. Raster-scanning optoacoustic mesoscopy for gastrointestinal imaging at high resolution. Gastroenterology 154, 807–809.e3 (2018).

    Google Scholar 

  69. Ahn, J., Kim, J. Y., Choi, W. & Kim, C. High-resolution functional photoacoustic monitoring of vascular dynamics in human fingers. Photoacoustics 23, 100282 (2021).

    MATH  Google Scholar 

  70. Wang, L. V. & Yao, J. A practical guide to photoacoustic tomography in the life sciences. Nat. Methods 13, 627–638 (2016).

    MATH  Google Scholar 

  71. Choi, W., Park, E.-Y., Jeon, S. & Kim, C. Clinical photoacoustic imaging platforms. Biomed. Eng. Lett. 8, 139–155 (2018).

    Google Scholar 

  72. Basij, M. et al. Miniaturized phased-array ultrasound and photoacoustic endoscopic imaging system. Photoacoustics 15, 100139 (2019).

    Google Scholar 

  73. Neuschmelting, V. et al. Performance of a multispectral optoacoustic tomography (MSOT) system equipped with 2D vs. 3D handheld probes for potential clinical translation. Photoacoustics 4, 1–10 (2016).

    Google Scholar 

  74. Kim, J. et al. Multiparametric photoacoustic analysis of human thyroid cancers in vivo. Cancer Res. 81, 4849–4860 (2021).

    MATH  Google Scholar 

  75. Neuschler, E. I. et al. A pivotal study of optoacoustic imaging to diagnose benign and malignant breast masses: a new evaluation tool for radiologists. Radiology 287, 398–412 (2018).

    MATH  Google Scholar 

  76. Choi, W. et al. Three-dimensional multistructural quantitative photoacoustic and US imaging of human feet in vivo. Radiology 303, 467–473 (2022).

    MATH  Google Scholar 

  77. Oraevsky, A. et al. Clinical optoacoustic imaging combined with ultrasound for coregistered functional and anatomical mapping of breast tumors. Photoacoustics 12, 30–45 (2018).

    Google Scholar 

  78. Liu, C. et al. In vivo transrectal imaging of canine prostate with a sensitive and compact handheld transrectal array photoacoustic probe for early diagnosis of prostate cancer. Biomed. Opt. Express 10, 1707–1717 (2019).

    MATH  Google Scholar 

  79. Kothapalli, S.-R. et al. Simultaneous transrectal ultrasound and photoacoustic human prostate imaging. Sci. Transl. Med. 11, eaav2169 (2019).

    Google Scholar 

  80. Asao, Y. et al. Photoacoustic mammography capable of simultaneously acquiring photoacoustic and ultrasound images. J. Biomed. Opt. 21, 116009 (2016).

    MATH  Google Scholar 

  81. Lin, L. et al. Single-breath-hold photoacoustic computed tomography of the breast. Nat. Commun. 9, 2352 (2018).

    MATH  Google Scholar 

  82. Chitgupi, U. et al. Surfactant‐stripped micelles for NIR‐II photoacoustic imaging through 12 cm of breast tissue and whole human breasts. Adv. Mater. 31, 1902279 (2019).

    Google Scholar 

  83. Na, S. et al. Massively parallel functional photoacoustic computed tomography of the human brain. Nat. Biomed. Eng. 6, 584–592 (2022).

    MATH  Google Scholar 

  84. Toi, M. et al. Visualization of tumor-related blood vessels in human breast by photoacoustic imaging system with a hemispherical detector array. Sci. Rep. 7, 41970 (2017).

    MATH  Google Scholar 

  85. He, H. et al. Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo. Nat. Commun. 13, 2803 (2022).

    MATH  Google Scholar 

  86. Aguirre, J. et al. Precision assessment of label-free psoriasis biomarkers with ultra-broadband optoacoustic mesoscopy. Nat. Biomed. Eng. 1, 0068 (2017).

    Google Scholar 

  87. Hindelang, B. et al. Enabling precision monitoring of psoriasis treatment by optoacoustic mesoscopy. Sci. Transl. Med. 14, eabm8059 (2022).

    Google Scholar 

  88. Mogensen, M., Thrane, L., Jørgensen, T. M., Andersen, P. E. & Jemec, G. B. OCT imaging of skin cancer and other dermatological diseases. J. Biophotonics 2, 442–451 (2009).

    Google Scholar 

  89. Koller, S. et al. In vivo reflectance confocal microscopy of erythematosquamous skin diseases. Exp. Dermatol. 18, 536–540 (2009).

    MATH  Google Scholar 

  90. König, K. et al. Translation of two-photon microscopy to the clinic: multimodal multiphoton CARS tomography of in vivo human skin. J. Biomed. Opt. 25, 014515 (2020).

    MATH  Google Scholar 

  91. Bhatta, A. K., Keyal, U. & Liu, Y. Application of high frequency ultrasound in dermatology. Discov. Med. 26, 237–242 (2018).

    MATH  Google Scholar 

  92. Attia, A. B. E. et al. Noninvasive real-time characterization of non-melanoma skin cancers with handheld optoacoustic probes. Photoacoustics 7, 20–26 (2017).

    MATH  Google Scholar 

  93. Chuah, S. et al. Structural and functional 3D mapping of skin tumours with non‐invasive multispectral optoacoustic tomography. Skin Res. Technol. 23, 221–226 (2017).

    MATH  Google Scholar 

  94. Ford, S. J. et al. Structural and functional analysis of intact hair follicles and pilosebaceous units by volumetric multispectral optoacoustic tomography. J. Invest. Dermatol. 136, 753–761 (2016).

    Google Scholar 

  95. Zhou, Y. et al. Handheld photoacoustic probe to detect both melanoma depth and volume at high speed in vivo. J. Biophotonics 8, 961–967 (2015).

    MATH  Google Scholar 

  96. Zhou, Y. et al. Noninvasive determination of melanoma depth using a handheld photoacoustic probe. J. Invest. Dermatol. 137, 1370 (2017).

    MATH  Google Scholar 

  97. Langley, R. G. & Ellis, C. N. Evaluating psoriasis with psoriasis area and severity index, psoriasis global assessment, and lattice system physician’s global assessment. J. Am. Acad. Dermatol. 51, 563–569 (2004).

    Google Scholar 

  98. Oji, V. & Luger, T. A. The skin in psoriasis: assessment and challenges. Clin. Exp. Rheumatol. 33, S14–19 (2015).

    MATH  Google Scholar 

  99. Ashcroft, D., Li Wan Po, A., Williams, H. & Griffiths, C. Clinical measures of disease severity and outcome in psoriasis: a critical appraisal of their quality. Br. J. Dermatol. 141, 185–191 (1999).

    Google Scholar 

  100. Marks, R. Measurement of the response to treatment in psoriasis. J. Dermatol. Treat. 7, S7–S10 (1996).

    MATH  Google Scholar 

  101. Griffiths, C. E. & Barker, J. N. Pathogenesis and clinical features of psoriasis. Lancet 370, 263–271 (2007).

    MATH  Google Scholar 

  102. Ryan, C. et al. Research gaps in psoriasis: opportunities for future studies. J. Am. Acad. Dermatol. 70, 146–167 (2014).

    MATH  Google Scholar 

  103. He, H. et al. Machine learning analysis of human skin by optoacoustic mesoscopy for automated extraction of psoriasis and aging biomarkers. IEEE Trans. Med. Imaging 43, 2074–2085 (2024).

    MATH  Google Scholar 

  104. Masthoff, M. et al. Multispectral optoacoustic tomography of systemic sclerosis. J. Biophotonics 11, e201800155 (2018).

    MATH  Google Scholar 

  105. Wilkinson, S. et al. Photoacoustic imaging is a novel tool to measure finger artery structure and oxygenation in patients with SSc. Sci. Rep. 12, 20446 (2022).

    MATH  Google Scholar 

  106. Nitkunanantharajah, S. et al. Three-dimensional optoacoustic imaging of nailfold capillaries in systemic sclerosis and its potential for disease differentiation using deep learning. Sci. Rep. 10, 16444 (2020).

    Google Scholar 

  107. Eisenbrey, J. R., Stanczak, M., Forsberg, F., Mendoza-Ballesteros, F. A. & Lyshchik, A. Photoacoustic oxygenation quantification in patients with Raynaud’s: first-in-human results. Ultrasound Med. Biol. 44, 2081–2088 (2018).

    Google Scholar 

  108. Yew, Y. W. et al. Investigation of morphological, vascular and biochemical changes in the skin of an atopic dermatitis (AD) patient in response to dupilumab using raster scanning optoacoustic mesoscopy (RSOM) and handheld confocal Raman spectroscopy (CRS). J. Dermatol. Sci. 95, 123–125 (2019).

    Google Scholar 

  109. Yew, Y. W. et al. Raster-scanning optoacoustic mesoscopy imaging as an objective disease severity tool in atopic dermatitis patients. J. Am. Acad. Dermatol. 84, 1121–1123 (2021).

    Google Scholar 

  110. Park, S. et al. Model learning analysis of 3D optoacoustic mesoscopy images for the classification of atopic dermatitis. Biomed. Opt. Express 12, 3671–3683 (2021).

    MATH  Google Scholar 

  111. Li, X. et al. Multispectral raster-scanning optoacoustic mesoscopy differentiate lesional from non-lesional atopic dermatitis skin using structural and functional imaging markers. Photoacoustics 28, 100399 (2022).

    MATH  Google Scholar 

  112. Nau, T. et al. Raster-scanning optoacoustic mesoscopy biomarkers for atopic dermatitis skin lesions. Photoacoustics 31, 100513 (2023).

    MATH  Google Scholar 

  113. Hindelang, B. et al. Optoacoustic mesoscopy shows potential to increase accuracy of allergy patch testing. Contact Dermat. 83, 206–214 (2020).

    Google Scholar 

  114. Gonzalez, E. A. & Bell, M. A. L. Photoacoustic imaging and characterization of bone in medicine: overview, applications, and outlook. Annu. Rev. Biomed. Eng. 25, 207–232 (2023).

    MATH  Google Scholar 

  115. Chamberland, D. L., Wang, X. & Roessler, B. J. Photoacoustic tomography of carrageenan-induced arthritis in a rat model. J. Biomed. Opt. 13, 011006 (2008).

    MATH  Google Scholar 

  116. Rajian, J. R., Shao, X., Chamberland, D. L. & Wang, X. Characterization and treatment monitoring of inflammatory arthritis by photoacoustic imaging: a study on adjuvant-induced arthritis rat model. Biomed. Opt. Express 4, 900–908 (2013).

    Google Scholar 

  117. Lutzweiler, C., Meier, R., Rummeny, E., Ntziachristos, V. & Razansky, D. Real-time optoacoustic tomography of indocyanine green perfusion and oxygenation parameters in human finger vasculature. Opt. Lett. 39, 4061–4064 (2014).

    Google Scholar 

  118. Keswani, R. K. et al. Repositioning clofazimine as a macrophage-targeting photoacoustic contrast agent. Sci. Rep. 6, 23528 (2016).

    MATH  Google Scholar 

  119. Wang, X., Chamberland, D. L. & Jamadar, D. A. Noninvasive photoacoustic tomography of human peripheral joints toward diagnosis of inflammatory arthritis. Opt. Lett. 32, 3002–3004 (2007).

    MATH  Google Scholar 

  120. Sun, Y., Sobel, E. & Jiang, H. Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study. J. Biomed. Opt. 14, 064005 (2009).

    MATH  Google Scholar 

  121. Xi, L. & Jiang, H. High resolution three-dimensional photoacoustic imaging of human finger joints in vivo. Appl. Phys. Lett. 107, 063701 (2015).

    MATH  Google Scholar 

  122. van Es, P., Biswas, S. K., Moens, H. J. B., Steenbergen, W. & Manohar, S. Initial results of finger imaging using photoacoustic computed tomography. J. Biomed. Opt. 19, 060501 (2014).

    MATH  Google Scholar 

  123. Xu, G. et al. Photoacoustic and ultrasound dual-modality imaging of human peripheral joints. J. Biomed. Opt. 18, 010502 (2013).

    MATH  Google Scholar 

  124. Yuan, J. et al. Real-time photoacoustic and ultrasound dual-modality imaging system facilitated with graphics processing unit and code parallel optimization. J. Biomed. Opt. 18, 086001 (2013).

    Google Scholar 

  125. Xiao, J. et al. Quantitative two-dimensional photoacoustic tomography of osteoarthritis in the finger joints. Opt. Express 18, 14359–14365 (2010).

    Google Scholar 

  126. van Es, P. et al. In European Conference on Biomedical Optics 95390C (Optica Publishing Group, 2015).

  127. Jo, J. et al. A functional study of human inflammatory arthritis using photoacoustic imaging. Sci. Rep. 7, 15026 (2017).

    MATH  Google Scholar 

  128. Zhao, C. et al. Multimodal photoacoustic/ultrasonic imaging system: a promising imaging method for the evaluation of disease activity in rheumatoid arthritis. Eur. Radiol. 31, 3542–3552 (2021).

    MATH  Google Scholar 

  129. Yang, M. et al. Synovial oxygenation at photoacoustic imaging to assess rheumatoid arthritis disease activity. Radiology 306, 220–228 (2023).

    Google Scholar 

  130. Kapuku, G. K. & Kop, W. J. In Handbook of Cardiovascular Behavioral Medicine 45–80 (Springer Nature, 2022).

  131. Günther, J. S. et al. Targeting muscular hemoglobin content for classification of peripheral arterial disease by noninvasive multispectral optoacoustic tomography. Cardiovasc. Imaging 16, 719–721 (2023).

    Google Scholar 

  132. Masthoff, M. et al. Use of multispectral optoacoustic tomography to diagnose vascular malformations. JAMA Dermatol. 154, 1457–1462 (2018).

    MATH  Google Scholar 

  133. Muller, J.-W. et al. Towards in vivo photoacoustic imaging of vulnerable plaques in the carotid artery. Biomed. Opt. Express 12, 4207–4218 (2021).

    MATH  Google Scholar 

  134. Ivankovic, I., Merčep, E., Schmedt, C.-G., Deán-Ben, X. L. & Razansky, D. Real-time volumetric assessment of the human carotid artery: handheld multispectral optoacoustic tomography. Radiology 291, 45–50 (2019).

    Google Scholar 

  135. Karlas, A. et al. Multispectral optoacoustic tomography of lipid and hemoglobin contrast in human carotid atherosclerosis. Photoacoustics 23, 100283 (2021).

    Google Scholar 

  136. Ganzleben, I. et al. Multispectral optoacoustic tomography for the non-invasive identification of patients with severe anemia in vivo. Photoacoustics 28, 100414 (2022).

    MATH  Google Scholar 

  137. Grünherz, L. et al. Preoperative mapping of lymphatic vessels by multispectral optoacoustic tomography. Lymphatic Res. Biol. 20, 659–664 (2022).

    Google Scholar 

  138. Giacalone, G., Yamamoto, T., Belva, F. & Hayashi, A. Bedside 3D visualization of lymphatic vessels with a handheld multispectral optoacoustic tomography device. J. Clin. Med. 9, 815 (2020).

    Google Scholar 

  139. Ahmed, M., Purushotham, A. D. & Douek, M. Novel techniques for sentinel lymph node biopsy in breast cancer: a systematic review. Lancet Oncol. 15, e351–e362 (2014).

    MATH  Google Scholar 

  140. Stoffels, I. et al. Metastatic status of sentinel lymph nodes in melanoma determined noninvasively with multispectral optoacoustic imaging. Sci. Transl. Med. 7, 317ra199 (2015).

    MATH  Google Scholar 

  141. Stoffels, I. et al. Assessment of nonradioactive multispectral optoacoustic tomographic imaging with conventional lymphoscintigraphic imaging for sentinel lymph node biopsy in melanoma. JAMA Netw. Open 2, e199020 (2019).

    MATH  Google Scholar 

  142. Regensburger, A. P. et al. Multispectral optoacoustic tomography for non-invasive disease phenotyping in pediatric spinal muscular atrophy patients. Photoacoustics 25, 100315 (2022).

    MATH  Google Scholar 

  143. Wagner, A. L. et al. Noninvasive imaging in pediatric spinal muscular atrophy patients using multispectral optoacoustic tomography: a proof-of-concept study. Neuropediatrics 52, S1–S53 (2021).

    MATH  Google Scholar 

  144. Karlas, A., Pleitez, M. A., Aguirre, J. & Ntziachristos, V. Optoacoustic imaging in endocrinology and metabolism. Nat. Rev. Endocrinol. 17, 323–335 (2021).

    MATH  Google Scholar 

  145. Roll, W. et al. Multispectral optoacoustic tomography of benign and malignant thyroid disorders: a pilot study. J. Nucl. Med. 60, 1461–1466 (2019).

    MATH  Google Scholar 

  146. He, H. et al. Opening a window to skin biomarkers for diabetes stage with optoacoustic mesoscopy. Light Sci. Appl. 12, 231 (2023).

    MATH  Google Scholar 

  147. Karlas, A. et al. Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage. Nat. Biomed. Eng. 7, 1667–1682 (2023).

    MATH  Google Scholar 

  148. Knieling, F. et al. Multispectral optoacoustic tomography for assessment of Crohn’s disease activity. N. Engl. J. Med. 376, 1292–1294 (2017).

    MATH  Google Scholar 

  149. Knieling, F. et al. Multispectral optoacoustic tomography in ulcerative colitis — a first-in-human diagnostic clinical trial. J. Nucl. Med. 58, 1196 (2017).

    MATH  Google Scholar 

  150. Regensburger, A. P. et al. Multispectral optoacoustic tomography enables assessment of disease activity in paediatric inflammatory bowel disease. Photoacoustics 35, 100578 (2024).

    MATH  Google Scholar 

  151. Ni, L. et al. Assessment of prostate cancer progression using a translational needle photoacoustic sensing probe: preliminary study with intact human prostates ex-vivo. Photoacoustics 28, 100418 (2022).

    MATH  Google Scholar 

  152. Abeyakoon, O. et al. An optoacoustic imaging feature set to characterise blood vessels surrounding benign and malignant breast lesions. Photoacoustics 27, 100383 (2022).

    Google Scholar 

  153. Manohar, S. & Dantuma, M. Current and future trends in photoacoustic breast imaging. Photoacoustics 16, 100134 (2019).

    Google Scholar 

  154. Lin, L. et al. Photoacoustic computed tomography of breast cancer in response to neoadjuvant chemotherapy. Adv. Sci. 8, 2003396 (2021).

    Google Scholar 

  155. Schoustra, S. M. et al. Twente photoacoustic mammoscope 2: system overview and three-dimensional vascular network images in healthy breasts. J. Biomed. Opt. 24, 121909 (2019).

    MATH  Google Scholar 

  156. Jafari, S. H. et al. Breast cancer diagnosis: imaging techniques and biochemical markers. J. Cell. Physiol. 233, 5200–5213 (2018).

    MATH  Google Scholar 

  157. Piras, D., Xia, W., Steenbergen, W., Van Leeuwen, T. G. & Manohar, S. Photoacoustic imaging of the breast using the Twente photoacoustic mammoscope: present status and future perspectives. IEEE J. Sel. Top. Quantum Electron. 16, 730–739 (2009).

    Google Scholar 

  158. Nyayapathi, N. et al. Dual scan mammoscope (DSM) — a new portable photoacoustic breast imaging system with scanning in craniocaudal plane. IEEE Trans. Biomed. Eng. 67, 1321–1327 (2019).

    MATH  Google Scholar 

  159. Li, X., Heldermon, C. D., Yao, L., Xi, L. & Jiang, H. High resolution functional photoacoustic tomography of breast cancer. Med. Phys. 42, 5321–5328 (2015).

    MATH  Google Scholar 

  160. Deán‐Ben, X. L., Fehm, T. F., Gostic, M. & Razansky, D. Volumetric hand‐held optoacoustic angiography as a tool for real‐time screening of dense breast. J. Biophotonics 9, 253–259 (2016).

    Google Scholar 

  161. Diot, G. et al. Multispectral optoacoustic tomography (MSOT) of human breast cancer. Clin. Cancer Res. 23, 6912–6922 (2017).

    MATH  Google Scholar 

  162. Vonk, J. et al. Multispectral optoacoustic tomography for in vivo detection of lymph node metastases in oral cancer patients using an EGFR-targeted contrast agent and intrinsic tissue contrast: a proof-of-concept study. Photoacoustics 26, 100362 (2022).

    MATH  Google Scholar 

  163. Noltes, M. E. et al. Towards in vivo characterization of thyroid nodules suspicious for malignancy using multispectral optoacoustic tomography. Eur. J. Nucl. Med. Mol. Imaging 50, 2736–2750 (2023).

    MATH  Google Scholar 

  164. Sharma, A., Srishti, Periyasamy, V. & Pramanik, M. Photoacoustic imaging depth comparison at 532-, 800-, and 1064-nm wavelengths: monte Carlo simulation and experimental validation. J. Biomed. Opt. 24, 121904 (2019).

    Google Scholar 

  165. Manwar, R., Lara, J. B., Prakash, R., Ranjbaran, S. M. & Avanaki, K. Randomized multi‐angle illumination for improved linear array photoacoustic computed tomography in brain. J. Biophotonics 15, e202200016 (2022).

    Google Scholar 

  166. Tzoumas, S. et al. Eigenspectra optoacoustic tomography achieves quantitative blood oxygenation imaging deep in tissues. Nat. Commun. 7, 12121 (2016).

    MATH  Google Scholar 

  167. Kirillin, M., Perekatova, V., Turchin, I. & Subochev, P. Fluence compensation in raster-scan optoacoustic angiography. Photoacoustics 8, 59–67 (2017).

    Google Scholar 

  168. Choi, W., Oh, D. & Kim, C. Practical photoacoustic tomography: realistic limitations and technical solutions. J. Appl. Phys. 127, 230903 (2020).

    MATH  Google Scholar 

  169. Chandramoorthi, S., Riksen, J. J., Nikolaev, A. V., Van Der Steen, A. F. & Van Soest, G. Wideband photoacoustic imaging in vivo with complementary frequency conventional ultrasound transducers. Front. Phys. https://doi.org/10.3389/fphy.2022.954537 (2022).

  170. Joseph, J., Ma, B. & Khuri-Yakub, B. Applications of capacitive micromachined ultrasonic transducers: a comprehensive review. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 69, 456–467 (2021).

    Google Scholar 

  171. Jung, J. et al. Review of piezoelectric micromachined ultrasonic transducers and their applications. J. Micromech. Microeng. 27, 113001 (2017).

    MATH  Google Scholar 

  172. Manwar, R., Kratkiewicz, K. & Avanaki, K. Overview of ultrasound detection technologies for photoacoustic imaging. Micromachines 11, 692 (2020).

    Google Scholar 

  173. Vallet, M. et al. Quantitative comparison of PZT and CMUT probes for photoacoustic imaging: experimental validation. Photoacoustics 8, 48–58 (2017).

    MATH  Google Scholar 

  174. Park, J. et al. Quadruple ultrasound, photoacoustic, optical coherence, and fluorescence fusion imaging with a transparent ultrasound transducer. Proc. Natl Acad. Sci. USA 118, e1920879118 (2021).

    Google Scholar 

  175. Chen, H. et al. A transparent ultrasound array for real-time optical, ultrasound, and photoacoustic imaging. BME Front. 2022, 9871098 (2022).

    Google Scholar 

  176. Ilkhechi, A. K., Ceroici, C., Li, Z. & Zemp, R. Transparent capacitive micromachined ultrasonic transducer (CMUT) arrays for real-time photoacoustic applications. Opt. express 28, 13750–13760 (2020).

    Google Scholar 

  177. Ansari, R., Zhang, E. Z., Desjardins, A. E. & Beard, P. C. All-optical forward-viewing photoacoustic probe for high-resolution 3D endoscopy. Light Sci. Appl. 7, 75 (2018).

    Google Scholar 

  178. Zhang, E., Laufer, J. & Beard, P. Backward-mode multiwavelength photoacoustic scanner using a planar Fabry-Perot polymer film ultrasound sensor for high-resolution three-dimensional imaging of biological tissues. Appl. Opt. 47, 561–577 (2008).

    Google Scholar 

  179. Ashkenazi, S., Chao, C.-Y., Guo, L. J. & O’Donnell, M. Ultrasound detection using polymer microring optical resonator. Appl. Phys. Lett. 85, 5418–5420 (2004).

    Google Scholar 

  180. Li, H., Dong, B., Zhang, Z., Zhang, H. F. & Sun, C. A transparent broadband ultrasonic detector based on an optical micro-ring resonator for photoacoustic microscopy. Sci. Rep. 4, 4496 (2014).

    MATH  Google Scholar 

  181. Hazan, Y., Levi, A., Nagli, M. & Rosenthal, A. Silicon-photonics acoustic detector for optoacoustic micro-tomography. Nat. Commun. 13, 1488 (2022).

    Google Scholar 

  182. Shnaiderman, R. et al. A submicrometre silicon-on-insulator resonator for ultrasound detection. Nature 585, 372–378 (2020).

    MATH  Google Scholar 

  183. Boktor, M. et al. Virtual histological staining of label-free total absorption photoacoustic remote sensing (TA-PARS). Sci. Rep. 12, 10296 (2022).

    MATH  Google Scholar 

  184. Ecclestone, B. R. et al. Label-free complete absorption microscopy using second generation photoacoustic remote sensing. Sci. Rep. 12, 8464 (2022).

    MATH  Google Scholar 

  185. Daoudi, K. et al. Handheld probe integrating laser diode and ultrasound transducer array for ultrasound/photoacoustic dual modality imaging. Opt. Express 22, 26365–26374 (2014).

    MATH  Google Scholar 

  186. Hariri, A. et al. The characterization of an economic and portable LED-based photoacoustic imaging system to facilitate molecular imaging. Photoacoustics 9, 10–20 (2018).

    MATH  Google Scholar 

  187. Zissis, G., Bertoldi, P. & Serrenho, T. Update on the Status of LED-Lighting World Market Since 2018 (Publications Office of the European Union, 2021).

  188. Li, L. The advances and characteristics of high-power diode laser materials processing. Opt. Lasers Eng. 34, 231–253 (2000).

    MATH  Google Scholar 

  189. Baribeau, Y. et al. Handheld point-of-care ultrasound probes: the new generation of POCUS. J. Cardiothorac. Vasc. Anesthesia 34, 3139–3145 (2020).

    MATH  Google Scholar 

  190. European Society of Radiology (ESR). Renewal of radiological equipment. Insights Imaging 5, 543–546 (2014).

    Google Scholar 

  191. Citron, P. Ethics considerations for medical device R&D. Prog. Cardiovasc. Dis. 55, 307–315 (2012).

    MATH  Google Scholar 

  192. Van der Burg, S. Imagining the future of photoacoustic mammography. Sci. Eng. Ethics 15, 97–110 (2009).

    MATH  Google Scholar 

  193. Mantri, Y. & Jokerst, J. V. Impact of skin tone on photoacoustic oximetry and tools to minimize bias. Biomed. Opt. Express 13, 875–887 (2022).

    Google Scholar 

  194. Else, T. R. et al. Effects of skin tone on photoacoustic imaging and oximetry. J. Biomed. Opt. 29, S11506 (2024).

    MATH  Google Scholar 

  195. Fernandes, G. S. et al. Mitigating skin tone bias in linear array in vivo photoacoustic imaging with short-lag spatial coherence beamforming. Photoacoustics 33, 100555 (2023).

    MATH  Google Scholar 

  196. Vogt, W. C., Wear, K. A. & Pfefer, T. J. Phantoms for evaluating the impact of skin pigmentation on photoacoustic imaging and oximetry performance. Biomed. Opt. Express 14, 5735–5748 (2023).

    MATH  Google Scholar 

  197. Abeyakoon, O. et al. Optoacoustic imaging detects hormone-related physiological changes of breast parenchyma. Ultraschall Med. 40, 757–763 (2019).

    Google Scholar 

  198. Steinberg, I. et al. Photoacoustic clinical imaging. Photoacoustics 14, 77–98 (2019).

    Google Scholar 

  199. Upputuri, P. K. & Pramanik, M. Recent advances toward preclinical and clinical translation of photoacoustic tomography: a review. J. Biomed. Opt. 22, 41006 (2017).

    Google Scholar 

  200. Schellenberg, M. W. & Hunt, H. K. Hand-held optoacoustic imaging: a review. Photoacoustics 11, 14–27 (2018).

    MATH  Google Scholar 

  201. Bohndiek, S. Addressing photoacoustics standards. Nat. Photonics 13, 298 (2019).

    Google Scholar 

  202. Assi, H. et al. A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: from current barriers to future adoption. Photoacoustics 32, 100539 (2023).

    MATH  Google Scholar 

  203. Beswick, D. M. et al. Biomedical device innovation methodology: applications in biophotonics. J. Biomed. Opt. https://doi.org/10.1117/1.JBO.23.2.021102 (2017).

  204. Marcu, L., Boppart, S. A., Hutchinson, M. R., Popp, J. & Wilson, B. C. Biophotonics: the big picture. J. Biomed. Opt. https://doi.org/10.1117/1.JBO.23.2.021103 (2017).

  205. Popp, J., Matthews, D., Martinez-Coll, A., Mayerhofer, T. & Wilson, B. C. Challenges in translation: models to promote translation. J. Biomed. Opt. https://doi.org/10.1117/1.JBO.23.2.021101 (2017).

  206. Gröhl, J., Hacker, L. & Cox, B. Photoacoustic data and device parameters. IPASC https://www.ipasc.science/wp-content/uploads/2023/01/20210916_IPASC_Format_V2.pdf (2021).

  207. Gröhl, J. et al. The IPASC data format: a consensus data format for photoacoustic imaging. Photoacoustics 26, 100339 (2022).

    MATH  Google Scholar 

  208. Deng, H., Qiao, H., Dai, Q. & Ma, C. Deep learning in photoacoustic imaging: a review. J. Biomed. Opt. 26, 040901 (2021).

    MATH  Google Scholar 

  209. Yang, C., Lan, H., Gao, F. & Gao, F. Review of deep learning for photoacoustic imaging. Photoacoustics 21, 100215 (2021).

    MATH  Google Scholar 

  210. Grohl, J., Schellenberg, M., Dreher, K. & Maier-Hein, L. Deep learning for biomedical photoacoustic imaging: a review. Photoacoustics 22, 100241 (2021).

    Google Scholar 

  211. Vogt, W. C. Proposed list of terms and definitions. IPASC https://www.ipasc.science/wp-content/uploads/2023/01/20191210_Terms_Definitions_For_PAT.pdf (2019).

  212. Goodsitt, M. M., Carson, P. L., Witt, S., Hykes, D. L. & Kofler, J. M. Jr. Real-time B-mode ultrasound quality control test procedures. Report of AAPM Ultrasound Task Group No. 1. Med. Phys. 25, 1385–1406 (1998).

    Google Scholar 

  213. Browne, J. E. Ultrasound elastography special issue. Ultrasound https://doi.org/10.1258/ult.2012.012e (2012).

  214. Hacker, L. et al. Criteria for the design of tissue-mimicking phantoms for the standardization of biophotonic instrumentation. Nat. Biomed. Eng. 6, 541–558 (2022).

    MATH  Google Scholar 

  215. Jia, C., Vogt, W. C., Wear, K. A., Pfefer, T. J. & Garra, B. S. Two-layer heterogeneous breast phantom for photoacoustic imaging. J. Biomed. Opt. https://doi.org/10.1117/1.JBO.22.10.106011 (2017).

  216. Vogt, W. C., Jia, C., Wear, K. A., Garra, B. S. & Pfefer, T. J. Phantom-based image quality test methods for photoacoustic imaging systems. J. Biomed. Opt. https://doi.org/10.1117/1.JBO.22.9.095002 (2017).

  217. Avigo, C. et al. Organosilicon phantom for photoacoustic imaging. J. Biomed. Opt. 20, 46008 (2015).

    Google Scholar 

  218. Cabrelli, L. C. et al. Glycerol-in-SEBS gel as a material to manufacture stable wall-less vascular phantom for ultrasound and photoacoustic imaging. Biomed. Phys. Eng. Express https://doi.org/10.1088/2057-1976/ac24d6 (2021).

  219. Hacker, L., Joseph, J., Lilaj, L. & Manohar, S. Recommendations for a photoacoustic phantom material. IPASC https://www.ipasc.science/wp-content/uploads/2023/06/IPASC-phantom-consensus-document.pdf (2023).

  220. Hacker, L. et al. A stable phantom material for optical and acoustic imaging. J. Vis. Exp. https://doi.org/10.3791/65475 (2023).

    Article  MATH  Google Scholar 

  221. Dogan, B. E. et al. Optoacoustic imaging and gray-scale US features of breast cancers: correlation with molecular subtypes. Radiology 292, 564–572 (2019).

    MATH  Google Scholar 

  222. Zalev, J. et al. In Photons Plus Ultrasound: Imaging and Sensing 2012 53–58 (SPIE, 2012).

  223. Neuschler, E. I. et al. Downgrading and upgrading gray-scale ultrasound BI-RADS categories of benign and malignant masses with optoacoustics: a pilot study. AJR Am. J. Roentgenol. 211, 689–700 (2018).

    Google Scholar 

  224. Seiler, S. J., Neuschler, E. I., Butler, R. S., Lavin, P. T. & Dogan, B. E. Optoacoustic imaging with decision support for differentiation of benign and malignant breast masses: a 15-reader retrospective study. AJR Am. J. Roentgenol. 220, 646–658 (2023).

    Google Scholar 

  225. Zalev, J. et al. Opto-acoustic imaging of relative blood oxygen saturation and total hemoglobin for breast cancer diagnosis. J. Biomed. Opt. 24, 1–16 (2019).

    Google Scholar 

  226. Food & Drug Administration. Information for Manufacturers Seeking Marketing Clearance of Diagnostic Ultrasound Systems and Transducers. Guidance for Industry and FDA Staff 1–64 (FDA, 2008).

  227. Ladd, M. E. The medical device regulation and its impact on device development and research in Germany. Z. für Medizinische Phys. 33, 459 (2023).

    MATH  Google Scholar 

  228. Singh, M. K. A. Cyberdyne, Inc.: CYBERDYNE AcousticX - A new paradigm in photoacoustic imaging. Presented at the SPIE BiOS Exhibition Product Demonstrations (SPIE, 2021).

  229. Ntziachristos, V. & Razansky, D. Molecular imaging by means of multispectral optoacoustic tomography (MSOT). Chem. Rev. 110, 2783–2794 (2010).

    MATH  Google Scholar 

  230. Jüstel, D. et al. Spotlight on nerves: portable multispectral optoacoustic imaging of peripheral nerve vascularization and morphology. Adv. Sci. 10, e2301322 (2023).

    MATH  Google Scholar 

  231. Karlas, A. et al. Skeletal muscle optoacoustics reveals patterns of circulatory function and oxygen metabolism during exercise. Photoacoustics 30, 100468 (2023).

    Google Scholar 

  232. Tsuge, I. et al. Preoperative vascular mapping for anterolateral thigh flap surgeries: a clinical trial of photoacoustic tomography imaging. Microsurgery 40, 324–330 (2020).

    MATH  Google Scholar 

  233. Matsumoto, Y. et al. Visualising peripheral arterioles and venules through high-resolution and large-area photoacoustic imaging. Sci. Rep. 8, 14930 (2018).

    Google Scholar 

  234. Cho, S., Jeon, S., Choi, W., Managuli, R. & Kim, C. Nonlinear pth root spectral magnitude scaling beamforming for clinical photoacoustic and ultrasound imaging. Opt. Lett. 45, 4575–4578 (2020).

    Google Scholar 

  235. Lin, L. et al. High-speed three-dimensional photoacoustic computed tomography for preclinical research and clinical translation. Nat. Commun. 12, 882 (2021).

    MATH  Google Scholar 

  236. Yao, J. et al. Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe. Nat. Methods 13, 67–73 (2016).

    MATH  Google Scholar 

  237. Jeon, S., Choi, W., Park, B. & Kim, C. A deep learning-based model that reduces speed of sound aberrations for improved in vivo photoacoustic imaging. IEEE Trans. Image Process. 30, 8773–8784 (2021).

    MATH  Google Scholar 

  238. Davoudi, N., Deán-Ben, X. L. & Razansky, D. Deep learning optoacoustic tomography with sparse data. Nat. Mach. Intell. 1, 453–460 (2019).

    MATH  Google Scholar 

  239. Chlis, N.-K. et al. A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography. Photoacoustics 20, 100203 (2020).

    MATH  Google Scholar 

  240. Zhang, J., Chen, B., Zhou, M., Lan, H. & Gao, F. Photoacoustic image classification and segmentation of breast cancer: a feasibility study. IEEE Access 7, 5457–5466 (2018).

    MATH  Google Scholar 

  241. Bai, B. et al. Deep learning-enabled virtual histological staining of biological samples. Light Sci. Appl. 12, 57 (2023).

    MATH  Google Scholar 

  242. Cao, R. et al. Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy. Nat. Biomed. Eng. 7, 124–134 (2023).

    MATH  Google Scholar 

  243. Qian, X., Zheng, Y. & Chen, Y. Micro/nanoparticle‐augmented sonodynamic therapy (SDT): breaking the depth shallow of photoactivation. Adv. Mater. 28, 8097–8129 (2016).

    MATH  Google Scholar 

  244. Suzuki, Y. et al. Photoacoustic lymphangiography exhibits advantages over near-infrared fluorescence lymphangiography as a diagnostic tool in patients with lymphedema. J. Vasc. Surgery Venous Lymphatic Disord. 10, 454–462.e1 (2022).

    MATH  Google Scholar 

  245. Wong, T. T. et al. Label-free automated three-dimensional imaging of whole organs by microtomy-assisted photoacoustic microscopy. Nat. Commun. 8, 1386 (2017).

    MATH  Google Scholar 

  246. Wong, T. T. et al. Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy. Sci. Adv. 3, e1602168 (2017).

    Google Scholar 

  247. Zhang, W. et al. Real-time, volumetric imaging of radiation dose delivery deep into the liver during cancer treatment. Nat. Biotechnol. 41, 1160–1167 (2023).

    MATH  Google Scholar 

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Acknowledgements

The authors’ work is supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1A6A1A03047902) and the Ministry of Science and ICT (2023R1A2C3004880); by the National R&D Program through the NRF funded by Ministry of Science and ICT (2021M3C1C3097624); by the Korea Medical Device Development Fund grant funded by the Korea Government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (9991007019, KMDF_PR_20200901_0008); and by the BK21 FOUR project. S.B. is supported by Cancer Research UK (C9545/A29580) and EPSRC (EP/R003599/1). IPASC are supported by EPSRC (EP/V027069/1).

Author information

Author notes

  1. These authors contributed equally: Jeongwoo Park, Seongwook Choi, Ferdinand Knieling.

Authors and Affiliations

  1. Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea

    Jeongwoo Park & Chulhong Kim

  2. Medical Device Innovation Center, POSTECH, Pohang, Republic of Korea

    Jeongwoo Park, Seongwook Choi & Chulhong Kim

  3. Department of Biomedical Convergence Science and Technology, School of Convergence, Kyungpook National University, Daegu, Republic of Korea

    Jeongwoo Park & Chulhong Kim

  4. Institute of Artificial Intelligence, POSTECH, Pohang, Republic of Korea

    Seongwook Choi

  5. Department of Pediatrics and Adolescent Medicine, University Hospital Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany

    Ferdinand Knieling

  6. Seno Medical Instruments, Inc., San Antonio, TX, USA

    Bryan Clingman

  7. Department of Physics, University of Cambridge, Cambridge, UK

    Sarah Bohndiek

  8. Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK

    Sarah Bohndiek

  9. Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology (CALTECH), Pasadena, CA, USA

    Lihong V. Wang

  10. Department of Electrical Engineering, CALTECH, Pasadena, CA, USA

    Lihong V. Wang

  11. Department of Convergence IT Engineering, POSTECH, Pohang, Republic of Korea

    Chulhong Kim

  12. Department of Mechanical Engineering, POSTECH, Pohang, Republic of Korea

    Chulhong Kim

  13. Department of Medical Science and Engineering, POSTECH, Pohang, Republic of Korea

    Chulhong Kim

  14. Opticho Inc., Pohang, Republic of Korea

    Chulhong Kim

Authors
  1. Jeongwoo Park
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  2. Seongwook Choi
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  3. Ferdinand Knieling
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  4. Bryan Clingman
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  5. Sarah Bohndiek
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  6. Lihong V. Wang
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Contributions

C.K., J.P., S.C., F.K. and B.C. researched data for the article. C.K., J.P., S.C. and F.K. contributed substantially to discussion of the content. C.K., J.P., S.C., F.K. and B.C. wrote the article. All authors reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Sarah Bohndiek, Lihong V. Wang or Chulhong Kim.

Ethics declarations

Competing interests

C.K. has financial interests in OPTICHO, which, however, did not support his work. B.C. has financial interests in Seno Medical Instruments, which, however, did not support his work. L.V.W. has a financial interest in Microphotoacoustics, Inc., CalPACT, LLC, and Union Photoacoustic Technologies, Ltd., which, however, did not support this work. F.K. has financial interests in iThera Medical GmbH, which, however, did not support his work. S.B. reports a relationship with iThera Medical GmbH that includes non-financial support. However, it did not support her work. The other authors declare no competing interests.

Peer review

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Nature Reviews Bioengineering thanks Liming Nie, Ivan Pelivanov and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Park, J., Choi, S., Knieling, F. et al. Clinical translation of photoacoustic imaging. Nat Rev Bioeng 3, 193–212 (2025). https://doi.org/10.1038/s44222-024-00240-y

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