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Single-impulse panoramic photoacoustic computed tomography of small-animal whole-body dynamics at high spatiotemporal resolution

Nature Biomedical Engineering volume 1, Article number: 0071 (2017) Cite this article

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Abstract

Imaging of small animals has played an indispensable role in preclinical research by providing high-dimensional physiological, pathological and phenotypic insights with clinical relevance. Yet, pure optical imaging suffers from either shallow penetration (up to ~1–2 mm) or a poor depth-to-resolution ratio (~3), and non-optical techniques for whole-body imaging of small animals lack either spatiotemporal resolution or functional contrast. Here, we demonstrate that stand-alone single-impulse panoramic photoacoustic computed tomography (SIP-PACT) mitigates these limitations by combining high spatiotemporal resolution (125 μm in-plane resolution, 50 μs per frame data acquisition and 50 Hz frame rate), deep penetration (48 mm cross-sectional width in vivo), anatomical, dynamical and functional contrasts, and full-view fidelity. Using SIP-PACT, we imaged in vivo whole-body dynamics of small animals in real time and obtained clear sub-organ anatomical and functional details. We tracked unlabelled circulating melanoma cells and imaged the vasculature and functional connectivity of whole rat brains. SIP-PACT holds great potential for both preclinical imaging and clinical translation.

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Figure 1: Schematics of the SIP-PACT system.
Figure 2: Label-free SIP-PACT of small-animal whole-body anatomy from the brain to the trunk.
Figure 3: Label-free imaging of small-animal whole-body dynamics.
Figure 4: SIP-PACT of mouse whole-body oxygenation dynamics.
Figure 5: Label-free tracking of CTCs in the mouse brain in vivo.
Figure 6: Deep imaging of rat whole-brain functions and whole-body anatomy.

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References

  1. Baker, M. Whole-animal imaging: the whole picture. Nature 463, 977–980 (2010).

    Article  CAS  Google Scholar 

  2. Zanzonico, P. in Small Animal Imaging: Basics and Practical Guide (eds Kiessling, F. & Pichler, J. B. ) 3–16 (Springer, 2011).

    Book  Google Scholar 

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

    Article  CAS  Google Scholar 

  4. Jun, X. & Wang, L. V. Small-animal whole-body photoacoustic tomography: a review. IEEE Trans. Biomed. Eng. 61, 1380–1389 (2014).

    Article  Google Scholar 

  5. Wu, D. & Zhang, J. In vivo mapping of macroscopic neuronal projections in the mouse hippocampus using high-resolution diffusion MRI. Neuroimage 125, 84–93 (2016).

    Article  Google Scholar 

  6. Alomair, O. I., Brereton, I. M., Smith, M. T., Galloway, G. J. & Kurniawan, N. D. In vivo high angular resolution diffusion-weighted imaging of mouse brain at 16.4 Tesla. PLoS ONE 10, e0130133 (2015).

    Article  Google Scholar 

  7. Schambach, S. J., Bag, S., Schilling, L., Groden, C. & Brockmann, M. A. Application of micro-CT in small animal imaging. Methods 50, 2–13 (2010).

    Article  CAS  Google Scholar 

  8. Brenner, D. J. & Hall, E. J. Computed tomography—an increasing source of radiation exposure. N. Engl. J. Med. 357, 2277–2284 (2007).

    Article  CAS  Google Scholar 

  9. Greco, A. et al. Ultrasound biomicroscopy in small animal research: applications in molecular and preclinical imaging. J. Biomed. Biotechnol. 2012, 519238 (2012).

    Article  CAS  Google Scholar 

  10. Kim, T. et al. White-light diffraction tomography of unlabelled live cells. Nat. Photon. 8, 256–263 (2014).

    Article  CAS  Google Scholar 

  11. Horton, N. G. et al. In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat. Photon. 7, 205–209 (2013).

    Article  CAS  Google Scholar 

  12. Zhang, F. et al. Multimodal fast optical interrogation of neural circuitry. Nature 446, 633–639 (2007).

    Article  CAS  Google Scholar 

  13. Darne, C., Lu, Y. & Sevick-Muraca, E. M. Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update. Phys. Med. Biol. 59, R1–R64 (2014).

    Article  Google Scholar 

  14. Razansky, D. et al. Multispectral opto-acoustic tomography of deep-seated fluorescent proteins in vivo . Nat. Photon. 3, 412–417 (2009).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  17. Jathoul, A. P. et al. Deep in vivo photoacoustic imaging of mammalian tissues using a tyrosinase-based genetic reporter. Nat. Photon. 9, 239–246 (2015).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  19. Brecht, H.-P. et al. Whole-body three-dimensional optoacoustic tomography system for small animals. J. Biomed. Opt. 14, 064007 (2009).

    Article  Google Scholar 

  20. Taruttis, A., Morscher, S., Burton, N. C., Razansky, D. & Ntziachristos, V. Fast multispectral optoacoustic tomography (MSOT) for dynamic imaging of pharmacokinetics and biodistribution in multiple organs. PLoS ONE 7, e30491 (2012).

    Article  CAS  Google Scholar 

  21. Merčep, E., Burton, N. C., Claussen, J. & Razansky, D. Whole-body live mouse imaging by hybrid reflection-mode ultrasound and optoacoustic tomography. Opt. Lett. 40, 4643–4646 (2015).

    Article  Google Scholar 

  22. Razansky, D., Buehler, A. & Ntziachristos, V. Volumetric real-time multispectral optoacoustic tomography of biomarkers. Nat. Protoc. 6, 1121–1129 (2011).

    Article  CAS  Google Scholar 

  23. Luis Dean-Ben, X. & Razansky, D. Adding fifth dimension to optoacoustic imaging: volumetric time-resolved spectrally enriched tomography. Light Sci. Appl. 3, e137 (2014).

    Article  Google Scholar 

  24. Tang, J., Coleman, J. E., Dai, X. & Jiang, H. Wearable 3-D photoacoustic tomography for functional brain imaging in behaving rats. Sci. Rep. 6, 25470 (2016).

    Article  Google Scholar 

  25. Yuan, X. & Wang, L. V. Effects of acoustic heterogeneity in breast thermoacoustic tomography. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 50, 1134–1146 (2003).

    Article  Google Scholar 

  26. Cohn, J. N. et al. Noninvasive pulse-wave analysis for the early detection of vascular-disease. Hypertension 26, 503–508 (1995).

    Article  CAS  Google Scholar 

  27. Kis, E. et al. Pulse wave velocity in end-stage renal disease: influence of age and body dimensions. Pediatr. Res. 63, 95–98 (2008).

    Article  Google Scholar 

  28. Stein, E. W., Maslov, K. & Wang, L. V. Noninvasive, in vivo imaging of blood-oxygenation dynamics within the mouse brain using photoacoustic microscopy. J. Biomed. Opt. 14, 020502 (2009).

    Article  Google Scholar 

  29. Xia, J. et al. Calibration-free quantification of absolute oxygen saturation based on the dynamics of photoacoustic signals. Opt. Lett. 38, 2800–2803 (2013).

    Article  CAS  Google Scholar 

  30. Raichle, M. E. Behind the scenes of functional brain imaging: a historical and physiological perspective. Proc. Natl Acad. Sci. USA 95, 765–772 (1998).

    Article  CAS  Google Scholar 

  31. Ogawa, S., Lee, T.-M., Kay, A. R. & Tank, D. W. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl Acad. Sci. USA 87, 9868–9872 (1990).

    Article  CAS  Google Scholar 

  32. Roberts, M. B. V. in Biology: A Functional Approach 4th edn, 243–249 (Thomas Nelson and Sons, 1986).

  33. Joiner, J. T. in NOAA Diving Manual: Diving For Science And Technology 4th edn, 1–36 (Best Publishing Company, 2001).

    Google Scholar 

  34. Karimova, A. & Pinsky, J. D. The endothelial response to oxygen deprivation: biology and clinical implications. Intensive Care Med. 27, 19–31 (2001).

    Article  CAS  Google Scholar 

  35. Piantadosi, C. A. in The Biology of Human Survival: Life and Death in Extreme Environments 129–139 (Oxford Univ. Press, 2003).

    Google Scholar 

  36. Miura, G. Cancer tumor imaging: catch me if you can. Nat. Chem. Biol. 10, 485–485 (2014).

    Google Scholar 

  37. Nagrath, S. et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 450, 1235–1239 (2007).

    Article  CAS  Google Scholar 

  38. Kienast, Y. et al. Real-time imaging reveals the single steps of brain metastasis formation. Nat. Med. 16, 116–122 (2010).

    Article  CAS  Google Scholar 

  39. Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2016. CA Cancer J. Clin. 66, 7–30 (2016).

    Article  Google Scholar 

  40. Srinivasan, V. J. et al. Quantitative cerebral blood flow with optical coherence tomography. Opt. Express 18, 2477–2494 (2010).

    Article  CAS  Google Scholar 

  41. Cox, S. B., Woolsey, T. A. & Rovainen, C. M. Localized dynamic changes in cortical blood flow with whisker stimulation corresponds to matched vascular and neuronal architecture of rat barrels. J. Cereb. Blood Flow Metab. 13, 899–913 (1993).

    Article  CAS  Google Scholar 

  42. Jonckers, E., Van Audekerke, J., De Visscher, G., Van der Linden, A. & Verhoye, M. Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse. PLoS ONE 6, e18876 (2011).

    Article  CAS  Google Scholar 

  43. Osmanski, B.-F., Pezet, S., Ricobaraza, A., Lenkei, Z. & Tanter, M. Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution. Nat. Commun. 5, 5023 (2014).

    Article  CAS  Google Scholar 

  44. Dean-Ben, X. L. et al. Functional optoacoustic neuro-tomography for scalable whole-brain monitoring of calcium indicators. Light Sci. Appl. 5, e16201 (2016).

    Article  CAS  Google Scholar 

  45. Gottschalk, S., Fehm, T. F., Deán-Ben, X. L. & Razansky, D. Noninvasive real-time visualization of multiple cerebral hemodynamic parameters in whole mouse brains using five-dimensional optoacoustic tomography. J. Cereb. Blood Flow Metab. 35, 531–535 (2015).

    Article  Google Scholar 

  46. Schackert, G., Price, J. E., Bucana, C. D. & Fidler, I. J. Unique patterns of brain metastasis produced by different human carcinomas in athymic nude mice. Int. J. Cancer 44, 892–897 (1989).

    Article  CAS  Google Scholar 

  47. Anastasio, M. A. et al. Half-time image reconstruction in thermoacoustic tomography. IEEE Trans. Med. Imaging 24, 199–210 (2005).

    Article  Google Scholar 

  48. Xu, M. & Wang, L. V. Universal back-projection algorithm for photoacoustic computed tomography. Phys. Rev. E 71, 016706 (2005).

    Article  Google Scholar 

  49. Treeby, B. E. & Cox, B. T. K-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields. J. Biomed. Opt. 15, 021314 (2010).

    Article  Google Scholar 

  50. Xia, J., Huang, C., Maslov, K., Anastasio, M. A. & Wang, L. V. Enhancement of photoacoustic tomography by ultrasonic computed tomography based on optical excitation of elements of a full-ring transducer array. Opt. Lett. 38, 3140–3143 (2013).

    Article  Google Scholar 

  51. Frangi, A. F., Niessen, W. J., Vincken, K. L. & Viergever, M. A. in International Conference on Medical Image Computing and Computer-Assisted Intervention (eds Wells, W. M., Colchester, A. & Delp, S. ) 130–137 (Springer, 1998).

    Google Scholar 

  52. Farnebäck, G. in Image Analysis (eds Bigun, J. & Gustavsson, T. ) 363–370 (Springer, 2003).

    Book  Google Scholar 

  53. White, B. R. et al. Imaging of functional connectivity in the mouse brain. PLoS ONE 6, e16322 (2011).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank Y. He, C. Li, Y. Li and J. Xia for their technical support, and J. Ballard for close reading of the manuscript. This work was sponsored by the United States National Institutes of Health (NIH) grants DP1 EB016986 (NIH Director’s Pioneer Award), R01 CA186567 (NIH Director’s Transformative Research Award), U01 NS090579 (BRAIN Initiative), U01 NS099717 (BRAIN Initiative), R01 EB016963 and S10 RR026922.

Author information

Author notes

  1. Cheng Ma

    Present address: Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China

  2. Junjie Yao

    Present address: Department of Biomedical Engineering, Duke University, Durham, North Carolina, 27708, USA

  3. Lidai Wang

    Present address: Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China

  4. Lei Li, Liren Zhu, Cheng Ma and Li Lin: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Electrical and Systems Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, 63130, Missouri, USA

    Lei Li

  2. Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, 91125, California, USA

    Lei Li, Liren Zhu, Li Lin, Konstantin Maslov, Junhui Shi & Lihong V. Wang

  3. Department of Biomedical Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, 63130, Missouri, USA

    Liren Zhu, Cheng Ma, Li Lin, Junjie Yao, Lidai Wang, Ruiying Zhang & Wanyi Chen

  4. Department of Electrical Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, 91125, California, USA

    Cheng Ma & Lihong V. Wang

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Contributions

L.Li and L.V.W. conceived and designed the study. L.Li and L.Z. constructed the hardware system. L.Li, L.Z. and C.M. developed the software system and the reconstruction algorithm. L.W. and J.S. constructed the control program. K.M. and W.C. designed the preamplifiers. L.Li, C.M. and L.Lin performed the experiments. R.Z. cultured the B16 cells. L.Li, L.Z., C.M. and J.Y. analysed the data. L.V.W. supervised the study. All authors contributed to the writing of the manuscript.

Corresponding author

Correspondence to Lihong V. Wang.

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Competing interests

L.V.W. and K.M. have a financial interest in Microphotoacoustics, Inc.; however, Microphotoacoustics, Inc. did not support this work. The other authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary figures, tables, references and video captions. (PDF 17806 kb)

Supplementary Video 1

In vivo label-free photoacoustic computed tomography of mouse internal organs. (MP4 47735 kb)

Supplementary Video 2

In vivo label-free photoacoustic computed tomography of a mouse's whole-body anatomy at a cross-section of the upper thoracic cavity. (MP4 18496 kb)

Supplementary Video 3

In vivo label-free photoacoustic computed tomography of mouse's whole-body anatomy at a cross-section of the lower thoracic cavity. (MP4 14849 kb)

Supplementary Video 4

In vivo label-free photoacoustic computed tomography of a mouse's whole-body anatomy at a cross-section of the liver. (MP4 5966 kb)

Supplementary Video 5

In vivo label-free photoacoustic computed tomography of a mouse's whole-body anatomy at a cross-section of the upper abdominal cavity. (MP4 6368 kb)

Supplementary Video 6

In vivo label-free photoacoustic computed tomography of a mouse's whole-body anatomy at a cross-section of the lower abdominal cavity. (MP4 13612 kb)

Supplementary Video 7

In vivo cross-sectional images of the mouse liver reconstructed by increasing angular coverage. (MP4 237 kb)

Supplementary Video 8

Pulse-wave-induced cross-sectional-area changes of two vertical arteries over time. (MP4 1761 kb)

Supplementary Video 9

In vivo label-free photoacoustic computed tomography of the mouse brain in response to an oxygen challenge. (MP4 3395 kb)

Supplementary Video 10

Oxygenation response of the lower abdominal cavity of a mouse during whole-body oxygen challenge. (MP4 7848 kb)

Supplementary Video 11

Label-free tracking of circulating melanoma tumour cells in the mouse brain in vivo. (MP4 8069 kb)

Supplementary Video 12

In vivo monitoring of dye perfusion in the mouse brain. (MP4 955 kb)

Supplementary Video 13

In vivo label-free photoacoustic computed tomography of rat whole-body anatomy at a cross-section of the lower abdominal cavity. (MP4 3008 kb)

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Li, L., Zhu, L., Ma, C. et al. Single-impulse panoramic photoacoustic computed tomography of small-animal whole-body dynamics at high spatiotemporal resolution. Nat Biomed Eng 1, 0071 (2017). https://doi.org/10.1038/s41551-017-0071

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