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  • Review Article
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Fluorescence image-guided tumour surgery

Nature Reviews Bioengineering volume 1, pages 161–179 (2023)Cite this article

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Abstract

Intraoperative fluorescent imaging can provide real-time identification of tumours, lymph nodes, nerves and other healthy and malignant tissues during oncological surgery, contributing to better surgical outcomes. Various fluorescent probes have been clinically approved for surgical applications, improving tumour resection precision and preventing iatrogenic injury. In this Review, we discuss the development and application of fluorescent probes for image-guided surgery, including systemically and locally applied probes that are either non-targeted or targeted to specific tumours and tissues. We discuss the optimization and clinical potential of these probes, and highlight their current and future applications in oncological surgery. In addition, we examine the hardware of fluorescence imaging equipment, and discuss how artificial intelligence can enable real-time quantification to guide surgical decision-making. Finally, we highlight the remaining challenges in the field of image-guided surgery, including the need for standardization to achieve regulatory approval of new probes, and the required team effort for new probe development.

Key points

  • Fluorescence image-guided surgery offers real-time intraoperative visualization of tumours and/or nearby healthy tissues, enabling high-precision tumour resection and prevention of iatrogenic injury.

  • Several fluorescence imaging probes have been clinically approved for oncological surgery, including non-targeted and tumour-targeted probes, and various new probes are being explored at the preclinical stage.

  • Hardware improvements and artificial intelligence software of intraoperative fluorescence imaging systems have improved imaging quality and enable image quantification, optimized ergonomics and straightforward human–machine interaction.

  • The clinical translation of new fluorescent imaging probes will require equipment standardization, interdisciplinary cooperation and technological development.

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Fig. 1: Major milestones in fluorescent probe development for oncological surgery.
Fig. 2: Fluorescent imaging probes in image-guided surgery.
Fig. 3: Intraoperative imaging in oncological surgery.
Fig. 4: Intraoperative fluorescence imaging of cancer tissue and nerves.

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Acknowledgements

The authors thank Z. Wang, X. Zhang and K. M. von Deneen for their advisory help with this article. The authors received support from the Ministry of Science and Technology of China under Grant No. 2017YFA0205200, the National Natural Science Foundation of China under Grant Nos 62027901, 92159305, 81930053, 81227901 and 82272029, the Beijing Science Fund under Grant No. JQ22013 and the Excellent Member Project of Youth Innovation Promotion Association CAS under Grant No. 2016124.

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  1. These authors contributed equally: Kun Wang, Yang Du, Zeyu Zhang.

Authors and Affiliations

  1. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Kun Wang, Yang Du, Lin Yin, Di Dong, Wei Li, Zhenhua Hu, Hui Hui, Chongwei Chi & Jie Tian

  2. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China

    Kun Wang, Yang Du, Lin Yin, Di Dong, Zhenhua Hu & Hui Hui

  3. Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Kun Wang, Yang Du, Lin Yin, Di Dong, Wei Li, Zhenhua Hu, Hui Hui, Chongwei Chi & Jie Tian

  4. State Key Laboratory Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Kun Wang, Yang Du, Lin Yin, Di Dong, Wei Li, Zhenhua Hu, Hui Hui, Chongwei Chi & Jie Tian

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

    Zeyu Zhang, Changjian Li & Jie Tian

  6. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Kunshan He

  7. Beijing Key Laboratory of Human–Computer Interaction, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Kunshan He

  8. Department of General Surgery, Capital Medical University, Beijing Friendship Hospital, Beijing, China

    Zhongquan Cheng

  9. Medical Imaging Center, the First Affiliated Hospital, Jinan University, Guangzhou, China

    Wei Li

  10. Department of Big Data Management and Application, School of International Economics and Management, Beijing Technology and Business University, Beijing, China

    Chong Zhang

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J.T. contributed to the conception of the Review. All authors contributed to the literature research, and to the writing and editing of this manuscript.

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Wang, K., Du, Y., Zhang, Z. et al. Fluorescence image-guided tumour surgery. Nat Rev Bioeng 1, 161–179 (2023). https://doi.org/10.1038/s44222-022-00017-1

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