Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows

Nature Biomedical Engineering volume 4, pages 259–271 (2020)Cite this article

Subjects

Abstract

The second near-infrared wavelength window (NIR-II, 1,000–1,700 nm) enables fluorescence imaging of tissue with enhanced contrast at depths of millimetres and at micrometre-scale resolution. However, the lack of clinically viable NIR-II equipment has hindered the clinical translation of NIR-II imaging. Here, we describe an optical-imaging instrument that integrates a visible multispectral imaging system with the detection of NIR-II and NIR-I (700–900 nm in wavelength) fluorescence (by using the dye indocyanine green) for aiding the fluorescence-guided surgical resection of primary and metastatic liver tumours in 23 patients. We found that, compared with NIR-I imaging, intraoperative NIR-II imaging provided a higher tumour-detection sensitivity (100% versus 90.6%; with 95% confidence intervals of 89.1%–100% and 75.0%–98.0%, respectively), a higher tumour-to-normal-liver-tissue signal ratio (5.33 versus 1.45) and an enhanced tumour-detection rate (56.41% versus 46.15%). We infer that combining the NIR-I/II spectral windows and suitable fluorescence probes might improve image-guided surgery in the clinic.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Description of the study plan and the visible and NIR-Ι/II multispectral imaging instrument for clinical applications.
Fig. 2: Comparison of the penetration and resolution of NIR-II and NIR-I imaging and the NIR-Ι/II image-guided tumour resection of subcutaneous HepG2 tumour-bearing mice.
Fig. 3: Intraoperative NIR-ΙI/I imaging of patients with primary HCC, intrahepatic metastasis or extrahepatic metastasis.
Fig. 4: Intraoperative NIR-I/II fluorescence image-guided tumour resection.
Fig. 5: Comparison of TNR or TBR for NIR-II and NIR-I imaging.
Fig. 6: Comparison of tumour-detection ability of NIR-I/II imaging.

Similar content being viewed by others

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets are available in figshare with the identifier https://doi.org/10.6084/m9.figshare.10316318 (ref. 39).

Code availability

Custom-developed code was applied to overlay the fluorescence signals on photographs. The raw MATLAB codes are available from the corresponding author upon request.

References

  1. James, M. L. & Gambhir, S. S. A molecular imaging primer: modalities, imaging agents, and applications. Physiol. Rev. 92, 897–965 (2012).

    Article  CAS  Google Scholar 

  2. Vahrmeijer, A. L., Hutteman, M., van der Vorst, J. R., van de Velde, C. J. & Frangioni, J. V. Image-guided cancer surgery using near-infrared fluorescence. Nat. Rev. Clin. Oncol. 10, 507–518 (2013).

    Article  CAS  Google Scholar 

  3. Vinegoni, C. et al. Indocyanine green enables near-infrared fluorescence imaging of lipid-rich, inflamed atherosclerotic plaques. Sci. Transl. Med. 3, 84ra45 (2011).

    Article  Google Scholar 

  4. Choi, H. S. et al. Targeted zwitterionic near-infrared fluorophores for improved optical imaging. Nat. Biotechnol. 31, 148–153 (2013).

    Article  CAS  Google Scholar 

  5. Tichauer, K. M. et al. Microscopic lymph node tumor burden quantified by macroscopic dual-tracer molecular imaging. Nat. Med. 20, 1348–1353 (2014).

    Article  CAS  Google Scholar 

  6. Pan, Y. et al. Endoscopic molecular imaging of human bladder cancer using a CD47 antibody. Sci. Transl. Med. 6, 260ra148 (2014).

    Article  Google Scholar 

  7. Miller, J. et al. Perfusion-based fluorescence imaging method delineates diverse organs and identifies multifocal tumors using generic near-infrared molecular probes. J. Biophoton. 11, e201700232 (2018).

    Article  Google Scholar 

  8. van Manen, L. et al. A practical guide for the use of indocyanine green and methylene blue in fluorescence-guided abdominal surgery. J. Surg. Oncol. 118, 283–300 (2018).

    Article  Google Scholar 

  9. Tipirneni, K. E. et al. Oncologic procedures amenable to fluorescence-guided surgery. Ann. Surg. 266, 36–47 (2017).

    Article  Google Scholar 

  10. Hutteman, M. et al. Randomized, double-blind comparison of indocyanine green with or without albumin premixing for near-infrared fluorescence imaging of sentinel lymph nodes in breast cancer patients. Breast Cancer Res. Treat. 127, 163–170 (2011).

    Article  CAS  Google Scholar 

  11. Gurtner, G. C. et al. Intraoperative laser angiography using the SPY system: review of the literature and recommendations for use. Ann. Surg. Innov. Res. 7, 1 (2013).

    Article  Google Scholar 

  12. Koller, M. et al. Implementation and benchmarking of a novel analytical framework to clinically evaluate tumor-specific fluorescent tracers. Nat. Commun. 9, 3739 (2018).

    Article  Google Scholar 

  13. Van Dam, G. M. et al. Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-α targeting: first in-human results. Nat. Med. 17, 1315–1319 (2011).

    Article  Google Scholar 

  14. Burggraaf, J. et al. Detection of colorectal polyps in humans using an intravenously administered fluorescent peptide targeted against c-Met. Nat. Med. 21, 955–961 (2015).

    Article  CAS  Google Scholar 

  15. Rosenthal, E. L. et al. Sensitivity and specificity of cetuximab-IRDye800CW to identify regional metastatic disease in head and neck cancer. Clin. Cancer Res. 23, 4744–4752 (2017).

    Article  CAS  Google Scholar 

  16. He, S., Song, J., Qu, J. & Cheng, Z. Crucial breakthrough of second near-infrared biological window fluorophores: design and synthesis toward multimodal imaging and theranostics. Chem. Soc. Rev. 47, 4258–4278 (2018).

    Article  CAS  Google Scholar 

  17. Hong, G., Antaris, A. L. & Dai, H. Near-infrared fluorophores for biomedical imaging. Nat. Biomed. Eng. 1, 0010 (2017).

    Article  CAS  Google Scholar 

  18. Dang, X. et al. Layer-by-layer assembled fluorescent probes in the second near-infrared window for systemic delivery and detection of ovarian cancer. Proc. Natl Acad. Sci. USA 113, 5179–5184 (2016).

    Article  CAS  Google Scholar 

  19. Hong, G. et al. Multifunctional in vivo vascular imaging using near-infrared II fluorescence. Nat. Med. 18, 1841–1846 (2012).

    Article  CAS  Google Scholar 

  20. Robinson, J. T. et al. In vivo fluorescence imaging in the second near-infrared window with long circulating carbon nanotubes capable of ultrahigh tumor uptake. J. Am. Chem. Soc. 134, 10664–10669 (2012).

    Article  CAS  Google Scholar 

  21. Hong, G. et al. Near-infrared II fluorescence for imaging hindlimb vessel regeneration with dynamic tissue perfusion measurement. Circ. Cardiovasc. Imaging 7, 517–525 (2014).

    Article  Google Scholar 

  22. Sun, Y. et al. Novel benzo-bis(1,2,5-thiadiazole) fluorophores for in vivo NIR-II imaging of cancer. Chem. Sci. 7, 6203–6207 (2016).

    Article  CAS  Google Scholar 

  23. Zhang, X. D. et al. Traumatic brain injury imaging in the second near-infrared window with a molecular fluorophore. Adv. Mater. 28, 6872–6879 (2016).

    Article  CAS  Google Scholar 

  24. Wang, R., Zhou, L., Wang, W., Li, X. & Zhang, F. In vivo gastrointestinal drug-release monitoring through second near-infrared window fluorescent bioimaging with orally delivered microcarriers. Nat. Commun. 8, 14702 (2017).

    Article  Google Scholar 

  25. Cheng, K. et al. Synthesis, characterization, and biomedical applications of a targeted dual-modal near-infrared-II fluorescence and photoacoustic imaging nanoprobe. ACS Nano 11, 12276–12291 (2017).

    Article  CAS  Google Scholar 

  26. Wan, H. et al. A bright organic NIR-II nanofluorophore for three-dimensional imaging into biological tissues. Nat. Commun. 9, 1171 (2018).

    Article  Google Scholar 

  27. Antaris, A. L. et al. A small-molecule dye for NIR-II imaging. Nat. Mater. 15, 235–242 (2016).

    Article  CAS  Google Scholar 

  28. Sun, Y. et al. Novel bright-emission small-molecule NIR-II fluorophores for in vivo tumor imaging and image-guided surgery. Chem. Sci. 8, 489–3493 (2017).

    Google Scholar 

  29. Sun, Y. et al. Novel dual-function near-infrared II fluorescence and PET probe for tumor delineation and image-guided surgery. Chem. Sci. 9, 2092–2097 (2018).

    Article  CAS  Google Scholar 

  30. Antaris, A. L. et al. A high quantum yield molecule-protein complex fluorophore for near-infrared II imaging. Nat. Commun. 8, 15269 (2017).

    Article  CAS  Google Scholar 

  31. Carr, J. A. et al. Shortwave infrared fluorescence imaging with the clinically approved near-infrared dye indocyanine green. Proc. Natl Acad. Sci. USA 115, 4465–4470 (2018).

    Article  CAS  Google Scholar 

  32. Starosolski, Z. et al. Indocyanine green fluorescence in second near-infrared (NIR-II) window. PLoS ONE 12, e0187563 (2017).

    Article  Google Scholar 

  33. Gotoh, K. et al. A novel image-guided surgery of hepatocellular carcinoma by indocyanine green fluorescence imaging navigation. J. Surg. Oncol. 100, 75–79 (2009).

    Article  Google Scholar 

  34. Ishizawa, T. et al. Real-time identification of liver cancers by using indocyanine green fluorescent imaging. Cancer 115, 2491–2504 (2009).

    Article  Google Scholar 

  35. Morita, Y. et al. Detection of hepatocellular carcinomas with near-infrared fluorescence imaging using indocyanine green: its usefulness and limitation. Int. J. Clin. Oncol. 18, 232–241 (2013).

    Article  CAS  Google Scholar 

  36. Ishizawa, T. et al. Mechanistic background and clinical applications of indocyanine green fluorescence imaging of hepatocellular carcinoma. Ann. Surg. Oncol. 21, 440–448 (2014).

    Article  Google Scholar 

  37. Shimada, S., Ohtsubo, S., Ogasawara, K. & Kusano, M. Macro- and microscopic findings of ICG fluorescence in liver tumors. World J. Surg. Oncol. 13, 198 (2015).

    Article  Google Scholar 

  38. Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0 (US Department of Health and Human Services, 2017); https://ctep.cancer.gov/protocolDevelopment/electronic_applications/docs/CTCAE_v5_Quick_Reference_8.5x11.pdf

  39. Hu, Z. et al. Dataset for first-in-human liver tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows. figshare https://doi.org/10.6084/m9.figshare.10316318 (2019).

Download references

Acknowledgements

This study was supported by the National Key Research and Development Program of China (2017YFA0205200, 2016YFC0102600), National Natural Science Foundation of China (NSFC) (81930053, 61622117, 81671759, 81227901), the Chinese Academy of Sciences (GJJSTD20170004), Beijing Natural Science Foundation (JQ19027), Beijing Nova Program (Z181100006218046), the Scientific Instrument Developing Project of the Chinese Academy of Sciences (YZ201672), the innovative research team of high-level local universities in Shanghai, and the Zhuhai High-level Health Personnel Team Project (Zhuhai HLHPTP201703). We acknowledge the instrumental and technical support of the multi-modal biomedical imaging experimental platform, Institute of Automation, Chinese Academy of Sciences.

Author information

Author notes

  1. These authors contributed equally: Zhenhua Hu, Cheng Fang, Bo Li, Zeyu Zhang.

Authors and Affiliations

  1. CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenhua Hu, Zeyu Zhang, Caiguang Cao, Meishan Cai, Xiaojing Shi, Cong Li, Chongwei Chi & Jie Tian

  2. University of Chinese Academy of Sciences, Beijing, China

    Zhenhua Hu, Caiguang Cao, Meishan Cai, Xiaojing Shi, Cong Li & Jie Tian

  3. Department of Hepatobiliary Surgery, Pathology and Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China

    Cheng Fang, Bo Li, Song Su, Xingwang Sun, Tiejun Zhou, Yuanxue Zhang, Pan He, Xianming Xia & Yue Chen

  4. Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China

    Zeyu Zhang & Jie Tian

  5. Molecular Imaging Program at Stanford, Bio-X Program, and Department of Radiology, Canary Center at Stanford for Cancer Early Detection, Stanford University, Stanford, CA, USA

    Sanjiv Sam Gambhir & Zhen Cheng

  6. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China

    Jie Tian

Authors
  1. Zhenhua Hu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Cheng Fang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Bo Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Zeyu Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Caiguang Cao
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Meishan Cai
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Song Su
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Xingwang Sun
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Xiaojing Shi
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Cong Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Tiejun Zhou
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Yuanxue Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Chongwei Chi
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Pan He
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Xianming Xia
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Yue Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Sanjiv Sam Gambhir
    View author publications

    You can also search for this author inPubMed Google Scholar

  18. Zhen Cheng
    View author publications

    You can also search for this author inPubMed Google Scholar

  19. Jie Tian
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

J.T., Z.C. and Z.H. conceived the idea of the project. Z.H. wrote the manuscript in addition to designing, performing and analysing all experiments. Z.H., C.F., B.L. and Z.Z. performed the experiments. S.S., P.H. and X.X. collected the information on patients with liver cancer. X. Sun., T.Z. and Y.Z. assisted with histology. Y.C. assisted with PET/CT imaging. C. Cao., M.C., X. Shi., C.L. and C. Chi. assisted with data analysis. Z.C. and S.S.G. assisted with experimental design, manuscript preparation and data/image analysis. J.T. designed, supervised and analysed all experiments, in addition to assisting with manuscript preparation.

Corresponding authors

Correspondence to Sanjiv Sam Gambhir, Zhen Cheng or Jie Tian.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary methods, figures and tables.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, Z., Fang, C., Li, B. et al. First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows. Nat Biomed Eng 4, 259–271 (2020). https://doi.org/10.1038/s41551-019-0494-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-019-0494-0

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research