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Fluorescence lifetime of injected indocyanine green as a universal marker of solid tumours in patients

Abstract

The surgical resection of solid tumours can be enhanced by fluorescence-guided imaging. However, variable tumour uptake and incomplete clearance of fluorescent dyes reduces the accuracy of distinguishing tumour from normal tissue via conventional fluorescence intensity-based imaging. Here we show that, after systemic injection of the near-infrared dye indocyanine green in patients with various types of solid tumour, the fluorescence lifetime (FLT) of tumour tissue is longer than the FLT of non-cancerous tissue. This tumour-specific shift in FLT can be used to distinguish tumours from normal tissue with an accuracy of over 97% across tumour types, and can be visualized at the cellular level using microscopy and in larger specimens through wide-field imaging. Unlike fluorescence intensity, which depends on imaging-system parameters, tissue depth and the amount of dye taken up by tumours, FLT is a photophysical property that is largely independent of these factors. FLT imaging with indocyanine green may improve the accuracy of cancer surgeries.

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Fig. 1: FLT enhancement and microscopic cancer specificity in primary and metastatic liver cancers.
Fig. 2: FLT enhancement and microscopic cancer specificity in HN cancers.
Fig. 3: FLT enhancement in primary and metastatic bone and soft tissue sarcomas.
Fig. 4: FLT enhancement in high-grade GBM.
Fig. 5: FLT imaging of tumour infiltrating LNs.
Fig. 6: Mechanistic studies of FLT enhancement in tumour cell lines.

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Data availability

The main data supporting the results in this study, including source data for the figures, are available within the paper and its Supplementary Information. The raw data generated in this study are too large to be publicly shared yet are available for research purposes on reasonable request from the corresponding author. The raw patient data are available from the corresponding author, subject to approval from the IRBs of the respective universities. Source data are provided with this paper.

Code availability

The custom MATLAB codes applied to analyse the TD fluorescence data are available from the corresponding author on reasonable request.

References

  1. Mieog, J. S. D. et al. Fundamentals and developments in fluorescence-guided cancer surgery. Nat. Rev. Clin. Oncol. 19, 9–22 (2022).

    Article  PubMed  CAS  Google Scholar 

  2. Lee, J. Y. K. et al. Review of clinical trials in intraoperative molecular imaging during cancer surgery. J. Biomed. Opt. 24, 120901 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lauwerends, L. J. et al. Real-time fluorescence imaging in intraoperative decision making for cancer surgery. Lancet Oncol. 22, e186–e195 (2021).

    Article  PubMed  CAS  Google Scholar 

  4. Gao, R. W. et al. Safety of panitumumab-IRDye800CW and cetuximab-IRDye800CW for fluorescence-guided surgical navigation in head and neck cancers. Theranostics 8, 2488 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Boogerd, L. S. F. et al. Safety and effectiveness of SGM-101, a fluorescent antibody targeting carcinoembryonic antigen, for intraoperative detection of colorectal cancer: a dose-escalation pilot study. Lancet Gastroenterol. Hepatol. 3, 181–191 (2018).

  6. Samkoe, K. S. et al. Preclinical imaging of epidermal growth factor receptor with ABY‐029 in soft‐tissue sarcoma for fluorescence‐guided surgery and tumor detection. J. Surg. Oncol. 119, 1077–1086 (2019).

  7. Hoogstins, C. E. S. et al. A novel tumor-specific agent for intraoperative near-infrared fluorescence imaging: a translational study in healthy volunteers and patients with ovarian cancer. Clin. Cancer Res. 22, 2929–2938 (2016).

  8. Shen, D. et al. Selective imaging of solid tumours via the calcium-dependent high-affinity binding of a cyclic octapeptide to phosphorylated Annexin A2. Nat. Biomed. Eng. 4, 298–313 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

  10. Schupper, A. J. et al. 5-Aminolevulinic acid for enhanced surgical visualization of high-grade gliomas: a prospective, multicenter study. J. Neurosurg. 136, 1525–1534 (2021).

  11. Veiseh, M. et al. Tumor paint: a chlorotoxin:Cy5.5 bioconjugate for intraoperative visualization of cancer foci. Cancer Res. 67, 6882–6888 (2007).

  12. Smith, B. L. et al. Real-time, intraoperative detection of residual breast cancer in lumpectomy cavity walls using a novel cathepsin-activated fluorescent imaging system. Breast Cancer Res. Treat. 171, 413–420 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Weissleder, R., Tung, C.-H., Mahmood, U. & Bogdanov, A Jr. In vivo imaging of tumors with protease-activated near-infrared fluorescent probes. Nat. Biotechnol. 17, 375–378 (1999).

  14. Pringle, T. A. et al. Synthesis and in vivo evaluation of a site-specifically labeled radioimmunoconjugate for dual-modal (PET/NIRF) imaging of MT1-MMP in sarcomas. Bioconjugate Chem. 33, 1564–1573 (2022).

    Article  CAS  Google Scholar 

  15. Petusseau, A. F., Bruza, P. & Pogue, B. W. Protoporphyrin IX delayed fluorescence imaging: a modality for hypoxia-based surgical guidance. J. Biomed. Opt. 27, 106005 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Chen, T., Chen, Z., Liu, R. & Zheng, S. A NIR fluorescent probe for detection of viscosity and lysosome imaging in live cells. Org. Biomol. Chem. 17, 6398–6403 (2019).

    Article  PubMed  CAS  Google Scholar 

  17. Song, Y. et al. One stone, three birds: pH triggered transformation of aminopyronine and iminopyronine based lysosome targeting viscosity probe for cancer visualization. Anal. Chem. 93, 1786–1791 (2020).

  18. Zhang, J. et al. A prostate-specific membrane antigen activated molecular rotor for real-time fluorescence imaging. Nat. Commun. 12, 5460 (2021).

  19. Zhao, T. et al. A transistor-like pH nanoprobe for tumour detection and image-guided surgery. Nat. Biomed. Eng. 1, 0006 (2016).

  20. Voskuil, F. J. et al. Exploiting metabolic acidosis in solid cancers using a tumor-agnostic pH-activatable nanoprobe for fluorescence-guided surgery. Nat. Commun. 11, 3257 (2020).

  21. Azari, F. et al. Intraoperative molecular imaging clinical trials: a review of 2020 conference proceedings. J. Biomed. Opt. 26, 050901 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Stummer, W. et al. Fluorescence-guided surgery with 5-aminolevulinic acid for resection of malignant glioma: a randomised controlled multicentre phase III trial. Lancet Oncol. 7, 392–401 (2006).

    Article  PubMed  CAS  Google Scholar 

  23. Valdés, P. A. et al. Quantitative fluorescence using 5-aminolevulinic acid-induced protoporphyrin IX biomarker as a surgical adjunct in low-grade glioma surgery. J. Neurosurg. 123, 771–780 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hadjipanayis, C. G. & Stummer, W. 5-ALA and FDA approval for glioma surgery. J. Neurooncol. 141, 479–486 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Schaafsma, B. E. et al. The clinical use of indocyanine green as a near-infrared fluorescent contrast agent for image-guided oncologic surgery. J. Surg. Oncol. 104, 323–332 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Barabino, G. et al. Intraoperative near-infrared fluorescence imaging using indocyanine green in colorectal carcinomatosis surgery: proof of concept. Eur. J. Surg. Oncol. 42, 1931–1937 (2016).

    Article  PubMed  CAS  Google Scholar 

  27. Liberale, G. et al. Indocyanine green fluorescence-guided surgery after IV injection in metastatic colorectal cancer: a systematic review. Eur. J. Surg. Oncol. 43, 1656–1667 (2017).

    Article  PubMed  CAS  Google Scholar 

  28. Zeh, R. et al. The second window ICG technique demonstrates a broad plateau period for near infrared fluorescence tumor contrast in glioblastoma. PLoS ONE 12, e0182034 (2017).

  29. Lee, J. Y. K. et al. Intraoperative near-infrared optical imaging can localize gadolinium-enhancing gliomas during surgery. Neurosurgery 79, 856–871 (2016).

  30. Yokoyama, J. et al. A feasibility study of NIR fluorescent image-guided surgery in head and neck cancer based on the assessment of optimum surgical time as revealed through dynamic imaging. Onco Targets Ther. 6, 325–330 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Veys, I. et al. ICG fluorescence imaging as a new tool for optimization of pathological evaluation in breast cancer tumors after neoadjuvant chemotherapy. PLoS ONE 13, e0197857 (2018).

  32. Nicoli, F. et al. Intraoperative near-infrared fluorescence (NIR) imaging with indocyanine green (ICG) can identify bone and soft tissue sarcomas which may provide guidance for oncological resection. Ann. Surg. 273, e63–e68 (2021).

    Article  PubMed  Google Scholar 

  33. Brookes, M. J. et al. Intraoperative near-infrared fluorescence guided surgery using indocyanine green (ICG) for the resection of sarcomas may reduce the positive margin rate: an extended case series. Cancers 13, 6284 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Horowitz, N. S. et al. Laparoscopy in the near infrared with ICG detects microscopic tumour in women with ovarian cancer: 0078. Int. J. Gynecol. Cancer 16, 622 (2006).

    Google Scholar 

  35. Kedrzycki, M. S. et al. The impact of temporal variation in indocyanine green administration on tumor identification during fluorescence guided breast surgery. Ann. Surg. Oncol. 28, 5617–5625 (2021).

  36. Onda, N., Kimura, M., Yoshida, T. & Shibutani, M. Preferential tumor cellular uptake and retention of indocyanine green for in vivo tumor imaging. Int. J. Cancer 139, 673–682 (2016).

  37. Kokudo, N. & Ishizawa, T. Clinical application of fluorescence imaging of liver cancer using indocyanine green. Liver Cancer 1, 15–21 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Pogue, B. W., Rosenthal, E. L., Achilefu, S. & Van Dam, G. M. Perspective review of what is needed for molecular-specific fluorescence-guided surgery. J. Biomed. Opt. 23, 100601 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Janku, F. Tumor heterogeneity in the clinic: is it a real problem? Ther. Adv. Med. Oncol. 6, 43–51 (2014).

  40. Pogue, B. W. & Rosenthal, E. L. Review of successful pathways for regulatory approvals in open-field fluorescence-guided surgery. J. Biomed. Opt. 26, 030901 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Lakowicz, J. R. Principles of Fluorescence Spectroscopy 2nd edn (Springer, 1999).

  42. Pal, R. & Kumar, A. T. N. Comparison of fluorescence lifetime and multispectral imaging for quantitative multiplexing in biological tissue. Biomed. Opt. Express 13, 3854–3868 (2022).

  43. Kumar, A. T. N. et al. Fluorescence lifetime-based contrast enhancement of indocyanine green-labeled tumors. J. Biomed. Opt. 22, 040501 (2017).

  44. Pal, R., Kang, H., Choi, H. S. & Kumar, A. T. N. Fluorescence lifetime-based tumor contrast enhancement using an EGFR antibody–labeled near-infrared fluorophore. Clin. Cancer Res. 25, 6653–6661 (2019).

  45. Cho, S. S. et al. Evaluation of diagnostic accuracy following the coadministration of delta-aminolevulinic acid and second window indocyanine green in rodent and human glioblastomas. Mol. Imaging Biol. 22, 1266–1279 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Nishio, N. et al. Optical molecular imaging can differentiate metastatic from benign lymph nodes in head and neck cancer. Nat. Commun. 10, 5044 (2019).

  47. Krishnan, G. et al. Metastatic and sentinel lymph node mapping using intravenously delivered Panitumumab-IRDye800CW. Theranostics 11, 7188–7198 (2021).

  48. Liao, K. et al. Viscosity effects on excited‐state dynamics of indocyanine green for phototheranostic. Chem. Asian J. 17, e202200112 (2022).

    Article  PubMed  CAS  Google Scholar 

  49. Chowdhury, R. et al. Excited state proton transfer in the lysosome of live lung cells: normal and cancer cells. J. Phys. Chem. B 119, 2149–2156 (2015).

    Article  PubMed  CAS  Google Scholar 

  50. Jung, B., Vullev, V. I. & Anvari, B. Revisiting indocyanine green: effects of serum and physiological temperature on absorption and fluorescence characteristics. IEEE J. Sel. Top. Quantum Electron. 20, 149–157 (2013).

    Article  Google Scholar 

  51. Berezin, M. Y., Lee, H., Akers, W. & Achilefu, S. Near infrared dyes as lifetime solvatochromic probes for micropolarity measurements of biological systems. Biophys. J. 93, 2892–2899 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Jiang, J. X. et al. Optimization of the enhanced permeability and retention effect for near-infrared imaging of solid tumors with indocyanine green. Am. J. Nucl. Med. Mol. Imaging 5, 390–400 (2015).

  53. Sarode, S. C. & Sarode, G. S. Real-time fluorescence imaging for cancer surgery: a pathologist’s perspective. Lancet Oncol. 22, e282 (2021).

    Article  PubMed  Google Scholar 

  54. Matikonda, S. S. et al. Impact of cyanine conformational restraint in the near-infrared range. J. Org. Chem. 85, 5907–5915 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Bishop, K. W., Maitland, K. C., Rajadhyaksha, M. & Liu, J. T. C. In vivo microscopy as an adjunctive tool to guide detection, diagnosis, and treatment. J. Biomed. Opt. 27, 040601 (2022).

  56. Orringer, D. A. et al. Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat. Biomed. Eng. 1, 0027 (2017).

  57. Patel, K. B. et al. High-speed light-sheet microscopy for the in-situ acquisition of volumetric histological images of living tissue. Nat. Biomed. Eng. 6, 569–583 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Berezin, M. Y. & Achilefu, S. Fluorescence lifetime measurements and biological imaging. Chem. Rev. 110, 2641–2684 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Bloch, S. et al. Whole-body fluorescence lifetime imaging of a tumor-targeted near-infrared molecular probe in mice. J. Biomed. Opt. 10, 054003 (2005).

  60. Goergen, C. J., Chen, H. H., Bogdanov, A., Sosnovik, D. E. & Kumar, A. T. N. In vivo fluorescence lifetime detection of an activatable probe in infarcted myocardium. J. Biomed. Opt. 17, 056001 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Ardeshirpour, Y. et al. In vivo fluorescence lifetime imaging monitors binding of specific probes to cancer biomarkers. PLoS ONE 7, e31881 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Rudkouskaya, A. et al. Multiplexed non-invasive tumor imaging of glucose metabolism and receptor-ligand engagement using dark quencher FRET acceptor. Theranostics 10, 10309–10325 (2020).

  63. Weyers, B. W. et al. Fluorescence lifetime imaging for intraoperative cancer delineation in transoral robotic surgery. Transl. Biophotonics 1, e201900017 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Durham, J. S. et al. Effect of fluorescence visualization-guided surgery on local recurrence of oral squamous cell carcinoma: a randomized clinical trial. JAMA Otolaryngol. Head Neck Surg. 146, 1149–1155 (2020).

  65. Erkkilä, M. T. et al. Macroscopic fluorescence-lifetime imaging of NADH and protoporphyrin IX improves the detection and grading of 5-aminolevulinic acid-stained brain tumors. Sci. Rep. 10, 20492 (2020).

  66. Alfonso-García, A. et al. First in patient assessment of brain tumor infiltrative margins using simultaneous time-resolved measurements of 5-ALA-induced PpIX fluorescence and tissue autofluorescence. J. Biomed. Opt. 27, 020501 (2022).

  67. Pal, R. et al. First clinical results of fluorescence lifetime-enhanced tumor imaging using receptor-targeted fluorescent probes. Clin. Cancer Res. 28, 2373–2384 (2022).

  68. Brunicardi, F. C. et al. Overview of the development of personalized genomic medicine and surgery. World J. Surg. 35, 1693–1699 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Walsh, E. M. et al. Fluorescence imaging of nerves during surgery. Ann. Surg. 270, 69–76 (2019).

    Article  PubMed  Google Scholar 

  70. Andreou, C., Weissleder, R. & Kircher, M. F. Multiplexed imaging in oncology. Nat. Biomed. Eng. 6, 527–540 (2022).

    Article  PubMed  Google Scholar 

  71. Sevick-Muraca, E. M. et al. Imaging of lymph flow in breast cancer patients after microdose administration of a near-infrared fluorophore: feasibility study. Radiology 246, 734–741 (2008).

  72. Sunar, U. et al. Noninvasive diffuse optical measurement of blood flow and blood oxygenation for monitoring radiation therapy in patients with head and neck tumors: a pilot study. J. Biomed. Opt. 11, 064021 (2006).

  73. Corlu, A. et al. Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans. Opt. Express 15, 6696–6716 (2007).

    Article  PubMed  Google Scholar 

  74. Poellinger, A. et al. Breast cancer: early- and late-fluorescence near-infrared imaging with indocyanine green—a preliminary study. Radiology 258, 409–416 (2011).

  75. Rice, W. L., Shcherbakova, D. M., Verkhusha, V. V. & Kumar, A. T. N. In vivo tomographic imaging of deep-seated cancer using fluorescence lifetime contrast. Cancer Res. 75, 1236–1243 (2015).

  76. Hu, Z. 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).

    Article  PubMed  Google Scholar 

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Acknowledgements

We acknowledge P. Isermann and D. Tom from Leica Microsystems, and the Harvard Medical School (Boston, MA) MicRoN for access to the Leica STELLARIS 8 used in this work, and for the extensive assistance in imaging. This work was supported in part by the NIH grants R01-CA211084, R01-CA260857 and 1P01CA240239 and the MGH-Executive Committee on Research Interim Support Fund.

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Authors and Affiliations

Authors

Contributions

R.P. designed and performed experiments and data analyses, in addition to co-writing the manuscript. T.M.L. assisted in clinical data acquisition, patient recruitment and project design. C.D.C. designed and performed experiments and analysed the data. T.H.D., H.R.C. and S.A.C. assisted in patient recruitment and IRB application; M.K., H.R.C. and S.S. performed experiments and data analysis, A.L.K. provided nursing services for the clinical study. S.A.C. and M.K. assisted with the imaging system design. M.P.N., A.P., M.S.M., Y.P.H., M.M.-L., L.Z., P.M.S., A.R.S. and W.C.F. provided pathology specimens and assisted in data interpretation. B.V.N., A.L.F., K.S.E., J.Y.K.L., K.S.R., S.L.-C., M.A.V., J.S.D.M, A.L.V., K.R. and K.K.T. provided surgical specimens and guidance in project design and data interpretation. A.T.N.K. conceived the idea for the project, designed and performed the experiments and data analysis, supervised the clinical studies and wrote the manuscript.

Corresponding author

Correspondence to Anand T. N. Kumar.

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Competing interests

A.T.N.K., M.K. and R.P. are co-inventors of a pending US Patent application issued to The General Hospital Corporation. The patent might be the subject of a licensing agreement in the future. Y.P.H. received royalties from Elsevier publishing company unrelated to this study. K.S.R. received remuneration for lecturing on a Stryker Fluorescence Guided Surgery Conference. The other authors declare no competing interests.

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Nature Biomedical Engineering thanks Jie Tian, Georg Widhalm and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Measurements of endogenous tissue autofluorescence in the NIR.

Photograph (a), fluorescence intensity (b), and FLT map (c) of a freshly resected metastatic colorectal cancer (mCRC) specimen without ICG injection. T, Tumor; N, Normal liver parenchyma. White dashed lines in a-c indicate the clinically defined tumor boundary. In the absence of ICG, the FLT of tumor autofluorescence (AF) was 0.22 ± 0.01 ns. Histology (d), confocal fluorescence intensity (e), and FLIM (f) images of a 10 µm OCT embedded tissue section obtained from a region of interest (a, yellow dotted outline). The mean tumor AF FLT measured via confocal FLIM was 0.37 ± 0.05 ns. g, Representative wide-field time domain (TD) fluorescence decay curves obtained from an mCRC specimen without ICG (green) and a specimen with ICG (red). The peak of the TD data (represented by the horizontal dashed lines) is representative of the fluorescence intensity in each mCRC tumor. Comparing the AF with tumor ICG intensity, we observed a nearly 20-times stronger signal in the ICG-injected specimen. h, Normalized plots of the TD data from (g), showing a significantly longer FLT of tumor-ICG (red = 0.61 ns) compared to the AF FLT (green = 0.22 ns), thus confirming that the tumor FLT observed with pre-surgery ICG administration arises from the tumor uptake of ICG.

Source data

Extended Data Fig. 2 FLT enhancement of a representative mCRC specimen from a clinical trial conducted at Leiden University.

Histology (a), fluorescence intensity (b), and FLIM (c) images of an mCRC specimen from a patient injected with 0.1 mg/kg ICG 24 h prior to surgery. Imaging was performed in 10 µm thick sections obtained from an FFPE tissue block. Histologically confirmed tumor boundary is shown in the histology (yellow line) and intensity (red line) images. The fluorescence intensity image (b) indicated ICG accumulation primarily around the tumor boundary (‘rim-fluorescence’). Despite the apparent absence of ICG, the FLT in the tumor core (0.74 ± 0.02 ns) was significantly longer (p < 0.001) than the surrounding normal liver parenchyma (0.61 ± 0.04 ns), indicating the presence of ICG in the tumor. Violin plots show the distribution of FLT, d, and intensity, e, across 18 ROIs obtained from the histologically determined tumor (11 ROIs), inflamed tumor stroma (3 ROIs), and normal hepatocyte regions (3 ROIs). f, ROC curves for tumor (tumor + inflamed tumor stroma) (14 ROIs) vs. normal tissue (15 ROIs) classification for this specimen yielded an accuracy (AUC) of 94% using fluorescence lifetime (red) and only 4% for intensity (green) based classification. The dashed lines in d and e represent the threshold FLT (0.68 ns) and intensity (42.7 AU), respectively, corresponding to the highest accuracy as calculated from the ROC curves.

Source data

Extended Data Fig. 3 FLT enhancement of a representative tongue SCC specimen.

Histology (a) and FLT (b) images of a tongue SCC specimen from a patient with ICG injection 20 h prior to surgery. Long FLT of ICG was observed to originate from the microscopic tumor nests (arrows) with short FLT components in the surrounding tissue. One such tumor cell nest (dotted rectangles in a and b) is shown with higher magnification in, c (histology) and d (FLT). c, the tumor nest (dashed outline) can be identified at the center of the histology image within a matrix of desmoplastic stroma and lymphocytes (dotted arrow). d, Long FLT was observed only in the tumor nest while the desmoplastic stroma and lymphocytes showed short FLT (dotted arrow). e, Histology, and f, FLT images of a buccal SCC specimen from another patient injected with ICG 20 h prior to surgery. The boundary of the tumor in the buccal epithelium can be identified by dashed lines in (e) and (f). The cancer cells clearly showed a longer FLT compared to the underlying muscle (solid arrows in (e) and (f)). The dotted arrows in (e) and (f) indicate tumor-infiltrating lymphocytes (TILs) with FLTs comparable to the tumor cells. g, Histology and h, FLT images of a normal oral epithelium showing low ICG uptake and short FLT across the epithelium (solid arrow) and the stroma (dashed arrow).

Extended Data Fig. 4 FLT enhancement of HN cancer specimens from a clinical trial conducted at the University of Pennsylvania.

FLT and intensity contrast in specimens from patients with HN cancer (n = 6) enrolled at the University of Pennsylvania with a high dose of ICG (5 mg/kg) are presented. Histology (a), fluorescence intensity (b), and FLT (c) images of a representative SCC of the tonsil with ICG injection 24 h prior to surgery. The dashed lines indicate histologically identified tumor-normal boundary. The patient-wise (n = 6) mean fluorescence intensity, d, and FLT, e, of tumor (red) and normal tissue (green) are shown as the mean of multiple ROIs ( > 30) of histologically identified tumor and normal tissue in each patient. Statistical significance was calculated using a t-test (two tailed, two sample of unequal variance): n.s. p > 0.05, *** p < 0.001. The average tumor FLTs for all 6 specimens ranged between 0.81–0.87 ns, which was within the FLT range observed with low dose ICG (0.74–0.92 ns) shown in Fig. 2j. The average normal tissue FLTs ranged between 0.72–0.78 ns, which was higher than the normal tissue FLT for the 0.5 mg/kg ICG dose (Fig. 2j; 0.45–0.68 ns) used at MGH, indicating a high non-specific ICG retention in normal tissue presumably due to a 5 mg/kg dose of ICG used in the trial at University of Pennsylvania. Violin plots showing the distribution of fluorescence intensity (f), and FLT (g) in HN tumors and normal tissue types across all 6 patients with high dose ICG. SG: salivary glands; NE: normal epithelium; NS: normal stroma. h, ROC plots of sensitivity vs. false positive rate (1 - specificity) across all patients studied (n = 6) resulted in an area under the curve (AUC) of 0.84 and 0.46 for FLT-based and intensity-based tumor vs normal classification, respectively. The grey-shaded areas represent 95% confidence interval.

Source data

Extended Data Fig. 5 FLT enhancement of breast cancer metastasis to the bone and osteosarcoma.

a, Histology, and b, confocal FLIM images of a specimen obtained from a patient with bone metastasis of breast cancer who was administered a flat dose of 50 mg ICG at the induction of anesthesia. c, Histology, and d, confocal FLIM images of a specimen collected from a patient with osteosarcoma systemically injected with 75 mg ICG one day before surgery. For both tumor types, the cancer cell nests are indicated by solid arrows (a and c) that correspond to long ICG FLT (b and d). Normal bone is indicated by dashed arrows in (a) that did not show a detectable ICG uptake (b). In the osteosarcoma specimen (c), large hemorrhagic pools of red blood cells (dashed arrows) were observed that displayed higher ICG fluorescence, but shorter FLT compared to the nearby cancer cell nests.

Extended Data Fig. 6 Normal tissue adjacent to sarcoma specimens show short ICG FLT.

Histology images of normal tissues, a, Skeletal muscle, b, epidermis with connective tissue, and c, adipose tissue obtained from a patient with myxofibrosarcoma ~2 h after systemic administration of ICG (0.5 mg/kg). Fresh normal tissue specimens away from the primary tumor were collected immediately following surgery and inking. Tissues were frozen in OCT overnight and sectioned (10 μm thickness) for confocal FLIM and H&E staining. A significant amount of connective tissue (red arrows) can be seen along with the epidermis (green arrows) in (b). Confocal FLIM images of the same sections of d, skeletal muscle, e, epidermis with connective tissue, and f, adipose tissues are shown. ICG FLTs in skeletal muscle, skin, connective tissue, and adipose tissue were 0.42 ns ± 0.04 ns, 0.41 ns ± 0.02 ns, 0.45 ns ± 0.01 ns, and 0.44 ± 0.02 ns, respectively. The long FLT component indicated by the ‘while arrowhead’ in (e) was considered an image artifact since it was not associated with the tissue (black arrowhead in (b)).

Extended Data Fig. 7 Wide-field FLT imaging of fresh human resection specimen from a patient with liposarcoma.

a, Photograph of a fresh resection specimen from a patient (S1 in Supplementary Table 13) with liposarcoma, 3 h after systemic ICG injection, showing clinically identified viable tumor (dashed red) and normal muscle (dashed green). Necrosis (solid arrow) and scar tissue (dotted arrow), formed due to extensive neo-adjuvant radiation therapy, are also visible in the FOV. b, Fluorescence intensity was highly heterogeneous within the tumor and significantly overlapped with the intensity of adjacent normal muscle, making it difficult to distinguish tumor from muscle. c, FLT maps clearly distinguished the tumor mass from normal muscle tissue. d, Representative wide-field TD fluorescence decay profiles of liposarcoma (red solid, 0.72 ± 0.07 ns), myxofibrosarcoma (red dashed, 0.73 ± 0.07 ns), and normal muscle (blue, 0.44 ± 0.04 ns) outside the clinically identified tumor margin. e, Fluorescence intensity, and f, FLT histograms of tumor (red) and normal muscle tissue (green) identified from the photograph in (a) are shown. A high degree of overlap of fluorescence intensities between the tumor and normal tissue was observed, while the tumor FLTs were distinctly longer than the normal tissue FLTs with minimal overlap.

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Supplementary dataset 1

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Supplementary dataset 2

Source data for Supplementary Fig. 3b.

Supplementary dataset 3

Source data for Supplementary Fig. 4b,d.

Supplementary dataset 4

Source data for Supplementary Fig. 5.

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Source Data Fig. 1

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Source Data Fig. 2

Source data and statistics.

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Pal, R., Lwin, T.M., Krishnamoorthy, M. et al. Fluorescence lifetime of injected indocyanine green as a universal marker of solid tumours in patients. Nat. Biomed. Eng 7, 1649–1666 (2023). https://doi.org/10.1038/s41551-023-01105-2

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