Breast Cancer Research and Treatment

, Volume 128, Issue 3, pp 679–689 | Cite as

Image-guided tumor resection using real-time near-infrared fluorescence in a syngeneic rat model of primary breast cancer

  • J. Sven D. Mieog
  • Merlijn Hutteman
  • Joost R. van der Vorst
  • Peter J. K. Kuppen
  • Ivo Que
  • Jouke Dijkstra
  • Eric L. Kaijzel
  • Frans Prins
  • Clemens W. G. M. Löwik
  • Vincent T. H. B. M. Smit
  • Cornelis J. H. van de Velde
  • Alexander L. Vahrmeijer
Preclinical study


Tumor involvement of resection margins is found in a large proportion of patients who undergo breast-conserving surgery. Near-infrared (NIR) fluorescence imaging is an experimental technique to visualize cancer cells during surgery. To determine the accuracy of real-time NIR fluorescence imaging in obtaining tumor-free resection margins, a protease-activatable NIR fluorescence probe and an intraoperative camera system were used in the EMR86 orthotopic syngeneic breast cancer rat model. Influence of concentration, timing and number of tumor cells were tested in the MCR86 rat breast cancer cell line. These variables were significantly associated with NIR fluorescence probe activation. Dosing and tumor size were also significantly associated with fluorescence intensity in the EMR86 rat model, whereas time of imaging was not. Real-time NIR fluorescence guidance of tumor resection resulted in a complete resection of 17 out of 17 tumors with minimal excision of normal healthy tissue (mean minimum and a mean maximum tumor-free margin of 0.2 ± 0.2 mm and 1.3 ± 0.6 mm, respectively). Moreover, the technique enabled identification of remnant tumor tissue in the surgical cavity. Histological analysis revealed that the NIR fluorescence signal was highest at the invasive tumor border and in the stromal compartment of the tumor. In conclusion, NIR fluorescence detection of breast tumor margins was successful in a rat model. This study suggests that clinical introduction of intraoperative NIR fluorescence imaging has the potential to increase the number of complete tumor resections in breast cancer patients undergoing breast-conserving surgery.


Near-infrared fluorescence imaging Image-guided surgery Breast conserving surgery Incomplete tumor resection Cathepsin 



Formalin fixed paraffin embedded





We want to thank Rob Keyzer and Anita Sajet for technical assistance and Fluoptics (Grenoble, France) for use of the Fluobeam® system. J.S.D. Mieog is a MD-medical research trainee funded by The Netherlands Organisation for Health Research and Development (grant nr. 92003526).

Supplementary material

Online Resource 1—Time-dependent activation of ProSense680 by MCR86 breast cancer rat cells: Fluorescence microscopy (LSM510 Zeiss confocal microscope, 40x objective) of a cluster of MCR86 cells. Images were acquired directly after incubation with ProSense680 (33.3 nM) up to 4.5 h thereafter. (MPG 1894 kb)

Online Resource 2—Intraoperative NIR fluorescence image-guided resection of primary breast cancer: Movie showing NIR fluorescence signal registered by the Fluobeam intraoperative camera system. Shown is a resection of an EMR86 tumor in a female WAG/Rij rat 24 h after intravenous administation of 10 nmol ProSense680. (MPG 6262 kb)

10549_2010_1130_MOESM3_ESM.pdf (346 kb)
Online Resource 3—Intraoperative NIR fluorescence detection of irradical resection of primary breast cancer: Shown is the capability of the Fluobeam camera system to detect remnant tumor tissue. Camera exposure time was 10 ms. a Intraoperative NIR fluorescence image of an intentionally irradical resection of an EMR86 tumor in a WAG/Rij rat 24 h after intravenous administration of 10 nmol ProSense680. A remnant fluorescent hotspot is readily visualized using intraoperative NIR fluorescence imaging. The identified fluorescent hotspot is resected under direct NIR fluorescence image-guidance. Resected hotspot is histologically confirmed as tumor tissue (H&E staining). (PDF 345 kb)


  1. 1.
    Mai KT, Yazdi HM, Isotalo PA (2000) Resection margin status in lumpectomy specimens of infiltrating lobular carcinoma. Breast Cancer Res Treat 60:29–33PubMedCrossRefGoogle Scholar
  2. 2.
    Chagpar AB, Martin RC, Hagendoorn LJ, Chao C, McMasters KM (2004) Lumpectomy margins are affected by tumor size and histologic subtype but not by biopsy technique. Am J Surg 188:399–402PubMedCrossRefGoogle Scholar
  3. 3.
    Smitt MC, Horst K (2007) Association of clinical and pathologic variables with lumpectomy surgical margin status after preoperative diagnosis or excisional biopsy of invasive breast cancer. Ann Surg Oncol 14:1040–1044PubMedCrossRefGoogle Scholar
  4. 4.
    Rizzo M, Iyengar R, Gabram SG et al (2010) The effects of additional tumor cavity sampling at the time of breast-conserving surgery on final margin status, volume of resection, and pathologist workload. Ann Surg Oncol 17:228–234PubMedCrossRefGoogle Scholar
  5. 5.
    Hewes JC, Imkampe A, Haji A, Bates T (2009) Importance of routine cavity sampling in breast conservation surgery. Br J Surg 96:47–53PubMedCrossRefGoogle Scholar
  6. 6.
    Clarke M, Collins R, Darby S et al (2005) Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials. Lancet 366:2087–2106PubMedGoogle Scholar
  7. 7.
    Nyirenda N, Farkas DL, Ramanujan VK. (2010) Preclinical evaluation of nuclear morphometry and tissue topology for breast carcinoma detection and margin assessment. Breast Cancer Res TreatGoogle Scholar
  8. 8.
    Stepp H, Beck T, Pongratz T et al (2007) ALA and malignant glioma: fluorescence-guided resection and photodynamic treatment. J Environ Pathol Toxicol Oncol 26:157–164PubMedCrossRefGoogle Scholar
  9. 9.
    Ishizawa T, Fukushima N, Shibahara J et al (2009) Real-time identification of liver cancers by using indocyanine green fluorescent imaging. Cancer 115:2491–2504PubMedCrossRefGoogle Scholar
  10. 10.
    Nguyen NQ, Biankin AV, Leong RW et al (2009) Real time intraoperative confocal laser microscopy-guided surgery. Ann Surg 249:735–737PubMedCrossRefGoogle Scholar
  11. 11.
    Frangioni JV (2008) New technologies for human cancer imaging. J Clin Oncol 26:4012–4021PubMedCrossRefGoogle Scholar
  12. 12.
    Mohamed MM, Sloane BF (2006) Cysteine cathepsins: multifunctional enzymes in cancer. Nat Rev Cancer 6:764–775PubMedCrossRefGoogle Scholar
  13. 13.
    Gocheva V, Zeng W, Ke D et al (2006) Distinct roles for cysteine cathepsin genes in multistage tumorigenesis. Genes Dev 20:543–556PubMedCrossRefGoogle Scholar
  14. 14.
    Parker BS, Ciocca DR, Bidwell BN et al (2008) Primary tumour expression of the cysteine cathepsin inhibitor Stefin A inhibits distant metastasis in breast cancer. J Pathol 214:337–346PubMedCrossRefGoogle Scholar
  15. 15.
    Harbeck N, Alt U, Berger U et al (2001) Prognostic impact of proteolytic factors (urokinase-type plasminogen activator, plasminogen activator inhibitor 1, and cathepsins B, D, and L) in primary breast cancer reflects effects of adjuvant systemic therapy. Clin Cancer Res 7:2757–2764PubMedGoogle Scholar
  16. 16.
    Lah TT, Kokalj-Kunovar M, Strukelj B et al (1992) Stefins and lysosomal cathepsins B, L, and D in human breast carcinoma. Int J Cancer 50:36–44PubMedCrossRefGoogle Scholar
  17. 17.
    Lah TT, Kos J, Blejec A et al (1997) The expression of lysosomal proteinases and their inhibitors in breast cancer: possible relationship to prognosis of the disease. Pathol Oncol Res 3:89–99PubMedCrossRefGoogle Scholar
  18. 18.
    Foekens JA, Kos J, Peters HA et al (1998) Prognostic significance of cathepsins B and L in primary human breast cancer. J Clin Oncol 16:1013–1021PubMedGoogle Scholar
  19. 19.
    Weissleder R, Tung CH, Mahmood U, Bogdanov A Jr (1999) In vivo imaging of tumors with protease-activated near-infrared fluorescent probes. Nat Biotechnol 17:375–378PubMedCrossRefGoogle Scholar
  20. 20.
    Kirsch DG, Dinulescu DM, Miller JB et al (2007) A spatially and temporally restricted mouse model of soft tissue sarcoma. Nat Med 13:992–997PubMedCrossRefGoogle Scholar
  21. 21.
    Bremer C, Tung CH, Bogdanov A Jr, Weissleder R (2002) Imaging of differential protease expression in breast cancers for detection of aggressive tumor phenotypes. Radiology 222:814–818PubMedCrossRefGoogle Scholar
  22. 22.
    von Burstin J, Eser S, Seidler B et al (2008) Highly sensitive detection of early-stage pancreatic cancer by multimodal near-infrared molecular imaging in living mice. Int J Cancer 123:2138–2147CrossRefGoogle Scholar
  23. 23.
    Sheth RA, Upadhyay R, Stangenberg L, Sheth R, Weissleder R, Mahmood U (2009) Improved detection of ovarian cancer metastases by intraoperative quantitative fluorescence protease imaging in a pre-clinical model. Gynecol Oncol 112:616–622PubMedCrossRefGoogle Scholar
  24. 24.
    Alencar H, Funovics MA, Figueiredo J, Sawaya H, Weissleder R, Mahmood U (2007) Colonic adenocarcinomas: near-infrared microcatheter imaging of smart probes for early detection–study in mice. Radiology 244:232–238PubMedCrossRefGoogle Scholar
  25. 25.
    Bogdanov AA Jr, Lin CP, Simonova M, Matuszewski L, Weissleder R (2002) Cellular activation of the self-quenched fluorescent reporter probe in tumor microenvironment. Neoplasia 4:228–236PubMedCrossRefGoogle Scholar
  26. 26.
    Niedre MJ, de Kleine RH, Aikawa E, Kirsch DG, Weissleder R, Ntziachristos V (2008) Early photon tomography allows fluorescence detection of lung carcinomas and disease progression in mice in vivo. Proc Natl Acad Sci USA 105:19126–19131PubMedCrossRefGoogle Scholar
  27. 27.
    Ntziachristos V, Tung CH, Bremer C, Weissleder R (2002) Fluorescence molecular tomography resolves protease activity in vivo. Nat Med 8:757–760PubMedCrossRefGoogle Scholar
  28. 28.
    Bremer C, Ntziachristos V, Weitkamp B, Theilmeier G, Heindel W, Weissleder R (2005) Optical imaging of spontaneous breast tumors using protease sensing ‘smart’ optical probes. Invest Radiol 40:321–327PubMedCrossRefGoogle Scholar
  29. 29.
    Gounaris E, Tung CH, Restaino C et al (2008) Live imaging of cysteine-cathepsin activity reveals dynamics of focal inflammation, angiogenesis, and polyp growth. PLoS One 3:e2916PubMedCrossRefGoogle Scholar
  30. 30.
    Grimm J, Kirsch DG, Windsor SD et al (2005) Use of gene expression profiling to direct in vivo molecular imaging of lung cancer. Proc Natl Acad Sci USA 102:14404–14409PubMedCrossRefGoogle Scholar
  31. 31.
    Nguyen QT, Olson ES, Aguilera TA et al (2010) Surgery with molecular fluorescence imaging using activatable cell-penetrating peptides decreases residual cancer and improves survival. Proc Natl Acad Sci USA 107:4317–4322PubMedCrossRefGoogle Scholar
  32. 32.
    van Dierendonck JH, Keijzer R, Cornelisse CJ, van de Velde CJ (1991) Surgically induced cytokinetic responses in experimental rat mammary tumor models. Cancer 68:759–767PubMedCrossRefGoogle Scholar
  33. 33.
    Wijsman JH, Cornelisse CJ, Keijzer R, van de Velde CJ, van Dierendonck JH (1991) A prolactin-dependent, metastasising rat mammary carcinoma as a model for endocrine-related tumour dormancy. Br J Cancer 64:463–468PubMedCrossRefGoogle Scholar
  34. 34.
    Sorlie T, Tibshirani R, Parker J et al (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100:8418–8423PubMedCrossRefGoogle Scholar
  35. 35.
    Sihto H, Lundin J, Lehtimaki T et al (2008) Molecular subtypes of breast cancers detected in mammography screening and outside of screening. Clin Cancer Res 14:4103–4110PubMedCrossRefGoogle Scholar
  36. 36.
    Mieog JS, Vahrmeijer AL, Hutteman M et al (2010) Novel intraoperative near-infrared fluorescence camera system for optical image-guided cancer surgery. Mol Imaging 9:223–231PubMedGoogle Scholar
  37. 37.
    Keramidas M, Josserand V, Righini CA, Wenk C, Faure C, Coll JL (2010) Intraoperative near-infrared image-guided surgery for peritoneal carcinomatosis in a preclinical experimental model. Br J Surg 97:737–743PubMedCrossRefGoogle Scholar
  38. 38.
    Mansfield JR, Hoyt C, Levenson RM (2008) Visualization of microscopy-based spectral imaging data from multi-label tissue sections. Curr Protoc Mol Biol, Chapter 14:UnitGoogle Scholar
  39. 39.
    Rasband WS, Image J (2009) US National Institutes of Health, Bethesda.
  40. 40.
    Juni P, Altman DG, Egger M (2001) Systematic reviews in health care: assessing the quality of controlled clinical trials. BMJ 323:42–46PubMedCrossRefGoogle Scholar
  41. 41.
    Kuester D, Lippert H, Roessner A, Krueger S (2008) The cathepsin family and their role in colorectal cancer. Pathol Res Pract 204:491–500PubMedCrossRefGoogle Scholar
  42. 42.
    Gocheva V, Joyce JA (2007) Cysteine cathepsins and the cutting edge of cancer invasion. Cell Cycle 6:60–64PubMedCrossRefGoogle Scholar
  43. 43.
    Troyan SL, Kianzad V, Gibbs-Strauss SL et al (2009) The FLARE intraoperative near-infrared fluorescence imaging system: a first-in-human clinical trial in breast cancer sentinel lymph node mapping. Ann Surg Oncol 16:2943–2952PubMedCrossRefGoogle Scholar
  44. 44.
    Hirche C, Murawa D, Mohr Z, Kneif S, Hunerbein M (2010) ICG fluorescence-guided sentinel node biopsy for axillary nodal staging in breast cancer. Breast Cancer Res Treat 121:373–378PubMedCrossRefGoogle Scholar
  45. 45.
    Kitai T, Inomoto T, Miwa M, Shikayama T (2005) Fluorescence navigation with indocyanine green for detecting sentinel lymph nodes in breast cancer. Breast Cancer 12:211–215PubMedCrossRefGoogle Scholar
  46. 46.
    Bloom S, Morrow M (2010) A clinical oncologic perspective on breast magnetic resonance imaging. Magn Reson Imaging Clin N Am 18:277–294 ixPubMedCrossRefGoogle Scholar
  47. 47.
    De Grand AM, Lomnes SJ, Lee DS et al (2006) Tissue-like phantoms for near-infrared fluorescence imaging system assessment and the training of surgeons. J Biomed Opt 11:014007PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • J. Sven D. Mieog
    • 1
  • Merlijn Hutteman
    • 1
  • Joost R. van der Vorst
    • 1
  • Peter J. K. Kuppen
    • 1
  • Ivo Que
    • 2
  • Jouke Dijkstra
    • 3
  • Eric L. Kaijzel
    • 2
  • Frans Prins
    • 4
  • Clemens W. G. M. Löwik
    • 2
  • Vincent T. H. B. M. Smit
    • 4
  • Cornelis J. H. van de Velde
    • 1
  • Alexander L. Vahrmeijer
    • 1
  1. 1.Department of SurgeryLeiden University Medical CenterLeidenThe Netherlands
  2. 2.Department of EndocrinologyLeiden University Medical CenterLeidenThe Netherlands
  3. 3.Department of Radiology Division of Image ProcessingLeiden University Medical CenterLeidenThe Netherlands
  4. 4.Department of PathologyLeiden University Medical CenterLeidenThe Netherlands

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