Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review
Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Literature Search and Study Selection
2.2. Data Extraction
2.3. Quality Assessment
3. Results
3.1. Overview of Included Studies
3.2. In Vivo Assessment of Lymph Nodes
3.3. Ex Vivo Assessment of Lymph Nodes
3.3.1. Ex Vivo Assessment During the Surgical Procedure
3.3.2. Ex Vivo Assessment After the Surgical Procedure
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
CEA | Carcinoembryonic Antigen |
CT | Computed Tomography |
EGFR | Endothelial Growth Factor Receptor |
FAPI | Fibroblast Activation Protein Inhibitor |
FFPE | Formalin-Fixed Paraffin-Embedded |
FI | Fluorescence Imaging |
H&E | Hematoxylin and Eosin |
HNC | Head and Neck Cancer |
LN | Lymph Node |
LNM | Lymph Node Metastasis |
MFI | Mean Fluorescence Intensity |
MRI | Magnetic Resonance Imaging |
MSOT | Multispectral Optoacoustic Tomography |
NIR | Near-Infrared |
OAI | Optoacoustic Imaging |
PET-CT | Positron Emission Tomography–Computed Tomography |
PRISMA | Preferred Reporting Items for Systematic Reviews and Meta-Analysis |
PSMA | Prostate-Specific Membrane Antigen |
SBR | Signal-to-Background Ratio |
SN | Sentinel Node |
SPECT-CT | Single Photon Emission Computed Tomography–Computed Tomography |
TBR | Tumor-to-Background Ratio |
VEGF-α | Vascular Endothelial Growth Factor Alpha |
Appendix A
Database Searched | via | Years of Coverage | Records | Records After Duplicates Removed |
---|---|---|---|---|
Embase | Embase.com | 1971–Present | 3645 | 3600 |
Medline ALL | Ovid | 1946–Present | 2942 | 617 |
Web of Science Core Collection * | Web of Knowledge | 1975–Present | 3628 | 1021 |
Cochrane Central Register of Controlled Trials | Wiley | 1992–Present | 48 | 28 |
Total | 10,263 | 5266 |
Appendix B
Section and Topic | Item # | Checklist Item | Location Where Item Is Reported |
---|---|---|---|
TITLE | |||
Title | 1 | Identify the report as a systematic review. | Page 1 |
ABSTRACT | |||
Abstract | 2 | See the PRISMA 2020 for Abstracts checklist. | Page 1–2 |
INTRODUCTION | |||
Rationale | 3 | Describe the rationale for the review in the context of existing knowledge. | Page 3 |
Objectives | 4 | Provide an explicit statement of the objective(s) or question(s) the review addresses. | Page 3 |
METHODS | |||
Eligibility criteria | 5 | Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. | Page 3–4 |
Information sources | 6 | Specify all databases, registers, websites, organizations, reference lists, and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted. | Page 3–4 |
Search strategy | 7 | Present the full search strategies for all databases, registers, and websites, including any filters and limits used. | Page 22–25 |
Selection process | 8 | Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and, if applicable, details of automation tools used in the process. | Page 3–4 |
Data collection process | 9 | Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from the study investigators, and, if applicable, details of automation tools used in the process. | Page 3–4 |
Data items | 10a | List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g., for all measures, time points, analyses), and, if not, the methods used to decide which results to collect. | Page 3–4 |
10b | List and define all other variables for which data were sought (e.g., participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information. | Page 3–4 | |
Study risk of bias assessment | 11 | Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and, if applicable, details of automation tools used in the process. | Page 22 |
Effect measures | 12 | Specify for each outcome the effect measure(s) (e.g., risk ratio, mean difference) used in the synthesis or presentation of results. | Page 22 |
Synthesis methods | 13a | Describe the processes used to decide which studies were eligible for each synthesis (e.g., tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). | Page 3–4 |
13b | Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions. | Page 3–4 | |
13c | Describe any methods used to tabulate or visually display results of individual studies and syntheses. | Page 3–4 | |
13d | Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used. | Page 3–4 | |
13e | Describe any methods used to explore possible causes of heterogeneity among the study results (e.g., subgroup analysis, meta-regression). | Page 3–4 | |
13f | Describe any sensitivity analyses conducted to assess robustness of the synthesized results. | Page 3–4 | |
Reporting bias assessment | 14 | Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). | Page 22 |
Certainty assessment | 15 | Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. | Page 22 |
RESULTS | |||
Study selection | 16a | Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram. | Page 3–4 |
16b | Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded. | Page 5 | |
Study characteristics | 17 | Cite each included study and present its characteristics. | Page 6–10 |
Risk of bias in studies | 18 | Present assessments of risk of bias for each included study. | Page 22 |
Results of individual studies | 19 | For all outcomes, present, for each study the (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g., confidence/credible interval), ideally using structured tables or plots. | Page 6–10 |
Results of syntheses | 20a | For each synthesis, briefly summarize the characteristics and risk of bias among contributing studies. | Page 22 |
20b | Present results of all statistical syntheses conducted. If meta-analysis was completed, present for each the summary estimate and its precision (e.g., confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect. | Page 6–10 | |
20c | Present results of all investigations of possible causes of heterogeneity among the study results. | Page 6–10 | |
20d | Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results. | Page 6–10 | |
Reporting biases | 21 | Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed. | Page 22 |
Certainty of evidence | 22 | Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed. | Page 22 |
DISCUSSION | |||
Discussion | 23a | Provide a general interpretation of the results in the context of other evidence. | Page 17–19 |
23b | Discuss any limitations of the evidence included in the review. | Page 17–19 | |
23c | Discuss any limitations of the review processes used. | Page 17–19 | |
23d | Discuss implications of the results for practice, policy, and future research. | Page 17–19 | |
OTHER INFORMATION | |||
Registration and protocol | 24a | Provide registration information for the review, including register name and registration number, or state that the review was not registered. | N/A |
24b | Indicate where the review protocol can be accessed, or state that a protocol was not prepared. | N/A | |
24c | Describe and explain any amendments to information provided at registration or in the protocol. | N/A | |
Support | 25 | Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review. | N/A |
Competing interests | 26 | Declare any competing interests of review authors. | N/A |
Availability of data, code, and other materials | 27 | Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review. | N/A |
Appendix C
References
- Fares, J.; Fares, M.Y.; Khachfe, H.H.; Salhab, H.A.; Fares, Y. Molecular principles of metastasis: A hallmark of cancer revisited. Signal Transduct. Target. Ther. 2020, 5, 28. [Google Scholar] [CrossRef]
- Edge, S.B.; Compton, C.C. The American Joint Committee on Cancer: The 7th edition of the AJCC cancer staging manual and the future of TNM. Ann. Surg. Oncol. 2010, 17, 1471–1474. [Google Scholar] [CrossRef]
- Mamelle, G.; Pampurik, J.; Luboinski, B.; Lancar, R.; Lusinchi, A.; Bosq, J. Lymph node prognostic factors in head and neck squamous cell carcinomas. Am. J. Surg. 1994, 168, 494–498. [Google Scholar] [CrossRef] [PubMed]
- Soerjomataram, I.; Louwman, M.W.; Ribot, J.G.; Roukema, J.A.; Coebergh, J.W. An overview of prognostic factors for long-term survivors of breast cancer. Breast Cancer Res. Treat. 2008, 107, 309–330. [Google Scholar] [CrossRef] [PubMed]
- Sürücü, E.; Polack, B.D.; Demir, Y.; Durmuşoğlu, M.; Ekmekçi, S.; Sarıoğlu, S.; Çelik, A.O.; Ada, E.; Iİkiz, A.Ö. Dual-phase F-18 FDG PET-CT in staging and lymphoscintigraphy for detection of sentinel lymph nodes in oral cavity cancers. Clin. Imaging. 2015, 39, 781–786. [Google Scholar] [CrossRef] [PubMed]
- García Megías, I.; Almeida, L.S.; Calapaquí Terán, A.K.; Pabst, K.M.; Herrmann, K.; Giammarile, F.; Bolton, R.C.D. FAPI radiopharmaceuticals in nuclear oncology and theranostics of solid tumours: Are we nearer to surrounding the hallmarks of cancer? Ann. Nucl. Med. 2025. [Google Scholar] [CrossRef]
- Baldari, L.; Boni, L.; Cassinotti, E. Lymph node mapping with ICG near-infrared fluorescence imaging: Technique and results. Minim. Invasive Ther. Allied Technol. 2023, 32, 213–221. [Google Scholar] [CrossRef]
- 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. 2013, 10, 507–518. [Google Scholar] [CrossRef]
- Van Manen, L.; Handgraaf, H.J.M.; Diana, M.; Dijkstra, J.; Ishizawa, T.; Vahrmeijer, A.L.; Mieog, J.S.D. A practical guide for the use of indocyanine green and methylene blue in fluorescence-guided abdominal surgery. J. Surg. Oncol. 2018, 118, 283–300. [Google Scholar] [CrossRef]
- Hernot, S.; van Manen, L.; Debie, P.; Mieog, J.S.D.; Vahrmeijer, A.L. Latest developments in molecular tracers for fluorescence image-guided cancer surgery. Lancet Oncol. 2019, 20, e354–e367. [Google Scholar] [CrossRef]
- Mieog, J.S.D.; Achterberg, F.B.; Zlitni, A.; Hutteman, M.; Burggraaf, J.; Swijnenburg, R.J.; Gioux, S.; Vahrmeijer, A.L. Fundamentals and developments in fluorescence-guided cancer surgery. Nat. Rev. Clin. Oncol. 2022, 19, 9–22. [Google Scholar] [CrossRef]
- Keereweer, S.; Van Driel, P.B.; Snoeks, T.J.; Kerrebijn, J.D.; Baatenburg de Jong, R.J.; Vahrmeijer, A.L.; Sterenborg, H.J.C.M.; Löwik, C.W.G.M. Optical image-guided cancer surgery: Challenges and limitations. Clin. Cancer Res. 2013, 19, 3745–3754. [Google Scholar] [CrossRef]
- Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, M.J.; Akl, A.E.; Brennan, E.S.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef] [PubMed]
- Whiting, P.; Rutjes, A.W.; Reitsma, J.B.; Bossuyt, P.M.; Kleijnen, J. The development of QUADAS: A tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med. Res. Methodol. 2003, 3, 25. [Google Scholar] [CrossRef] [PubMed]
- Hoogstins, C.E.S.; Tummers, Q.R.J.G.; Gaarenstroom, K.N.; De Kroon, C.D.; Trimbos, J.B.M.Z.; Bosse, T.; Smit, V.T.; Vuyk, J.; van de Velde, C.J.; Cohen, A.F.; 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. 2016, 22, 2929–2938. [Google Scholar] [CrossRef] [PubMed]
- Tummers, Q.R.J.G.; Hoogstins, C.E.S.; Gaarenstroom, K.N.; de Kroon, C.D.; van Poelgeest, M.I.E.; Vuyk, J.; Bosse, T.; Smit, V.T.; van de Velde, C.J.; Cohen, A.F.; et al. Intraoperative imaging of folate receptor alpha positive ovarian and breast cancer using the tumor specific agent EC17. Oncotarget 2016, 7, 32144–32155. [Google Scholar] [CrossRef]
- Lamberts, L.E.; Koch, M.; De Jong, J.S.; Adams, A.L.L.; Glatz, J.; Kranendonk, M.E.G.; Van Scheltinga, A.G.T.; Jansen, L.; De Vries, J.; Hooge, M.N.L.-D.; et al. Tumor-specific uptake of fluorescent bevacizumab-IRDye800CW microdosing in patients with primary breast cancer: A phase I feasibility study. Clin. Cancer Res. 2017, 23, 2730–2741. [Google Scholar] [CrossRef] [PubMed]
- Rosenthal, E.L.; Moore, L.S.; Tipirneni, K.; De Boer, E.; Stevens, T.M.; Hartman, Y.E.; Carroll, W.R.; Zinn, K.R.; Warram, J.M. Sensitivity and specificity of cetuximab-IRDye800CW to identify regional metastatic disease in head and neck cancer. Clin. Cancer Res. 2017, 23, 4744–4752. [Google Scholar] [CrossRef]
- Unkart, J.T.; Chen, S.L.; Wapnir, I.L.; Gonzalez, J.E.; Harootunian, A.; Wallace, A.M. Intraoperative Tumor Detection Using a Ratiometric Activatable Fluorescent Peptide: A First-in-Human Phase 1 Study. Ann. Surg. Oncol. 2017, 24, 3167–3173. [Google Scholar] [CrossRef]
- Boogerd, L.S.F.; Hoogstins, C.E.S.; Gaarenstroom, K.N.; de Kroon, C.D.; Beltman, J.J.; Bosse, T.; Stelloo, E.; Vuyk, J.; Low, P.S.; Burggraaf, J.; et al. Folate receptor-α targeted near-infrared fluorescence imaging in high-risk endometrial cancer patients: A tissue microarray and clinical feasibility study. Oncotarget 2018, 9, 791–801. [Google Scholar] [CrossRef]
- Boogerd, L.S.F.; Hoogstins, C.E.S.; Schaap, D.P.; Kusters, M.; Handgraaf, H.J.M.; van der Valk, M.J.M.; E Hilling, D.; A Holman, F.; Peeters, K.C.M.J.; Mieog, J.S.D.; 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. 2018, 3, 181–191. [Google Scholar] [CrossRef] [PubMed]
- Tummers, W.S.; Miller, S.E.; Teraphongphom, N.T.; Gomez, A.; Steinberg, I.; Huland, D.M.; Hong, S.; Kothapalli, S.-R.; Hasan, A.; Ertsey, R.; et al. Intraoperative Pancreatic Cancer Detection using Tumor—Specific Multimodality Molecular Imaging. Ann. Surg. Oncol. 2018, 25, 1880–1888. [Google Scholar] [CrossRef] [PubMed]
- Hoogstins, C.E.S.; Boogerd, L.S.F.; Gaarenstroom, K.N.; de Kroon, C.D.; Beltman, J.J.; Trimbos, J.B.M.Z.; Bosse, T.; Vuyk, J.; Low, P.S.; Burggraaf, J.; et al. Feasibility of folate receptor-targeted intraoperative fluorescence imaging during staging procedures for early ovarian cancer. Eur. J. Gynaecol. Oncol. 2019, 40, 203–208. [Google Scholar] [CrossRef]
- Nishio, N.; van den Berg, N.S.; van Keulen, S.; Martin, B.A.; Fakurnejad, S.; Teraphongphom, N.; Chirita, S.U.; Oberhelman, N.J.; Lu, G.; Horton, C.E.; et al. Optical molecular imaging can differentiate metastatic from benign lymph nodes in head and neck cancer. Nat. Commun. 2019, 10, 5044. [Google Scholar] [CrossRef]
- Randall, L.M.; Wenham, R.M.; Low, P.S.; Dowdy, S.C.; Tanyi, J.L. A phase II, multicenter, open-label trial of OTL38 injection for the intra-operative imaging of folate receptor-alpha positive ovarian cancer. Gynecol. Oncol. 2019, 155, 63–68. [Google Scholar] [CrossRef]
- Tummers, W.S.; Miller, S.E.; Teraphongphom, N.T.; van den Berg, N.S.; Hasan, A.; Longacre, T.A.; Fisher, G.A.; Bonsing, B.A.; Vahrmeijer, A.L.; Gambhir, S.S.; et al. Detection of visually occult metastatic lymph nodes using molecularly targeted fluorescent imaging during surgical resection of pancreatic cancer. HPB 2019, 21, 883–890. [Google Scholar] [CrossRef]
- De Jongh, S.J.; Tjalma, J.J.J.; Koller, M.; Linssen, M.D.; Vonk, J.; Dobosz, M.; Jorritsma-Smit, A.; Kleibeuker, J.H.; Hospers, G.A.; Havenga, K.; et al. Back-Table Fluorescence-Guided Imaging for Circumferential Resection Margin Evaluation Using Bevacizumab-800CW in Patients with Locally Advanced Rectal Cancer. J. Nucl. Med. 2020, 61, 655–661. [Google Scholar] [CrossRef]
- De Valk, K.S.; Deken, M.M.; Handgraaf, H.J.M.; Bhairosingh, S.S.; Bijlstra, O.D.; van Esdonk, M.J.; van Scheltinga, A.G.T.; Valentijn, A.R.P.; March, T.L.; Vuijk, J.; et al. First-in-Human Assessment of cRGD-ZW800-1, a Zwitterionic, Integrin-Targeted, Near-Infrared Fluorescent Peptide in Colon Carcinoma. Clin. Cancer Res. 2020, 26, 3990–3998. [Google Scholar] [CrossRef]
- Lu, G.; van den Berg, N.S.; Martin, B.A.; Nishio, N.; Hart, Z.P.; van Keulen, S.; Fakurnejad, S.; Chirita, S.U.; Raymundo, R.C.; Yi, G.; et al. Tumour-specific fluorescence-guided surgery for pancreatic cancer using panitumumab-IRDye800CW: A phase 1 single-centre, open-label, single-arm, dose-escalation study. Lancet Gastroenterol. Hepatol. 2020, 5, 753–764. [Google Scholar] [CrossRef]
- Aras, O.; Demirdag, C.; Kommidi, H.; Guo, H.; Pavlova, I.; Aygun, A.; Karayel, E.; Pehlivanoglu, H.; Yeyin, N.; Kyprianou, N.; et al. Small Molecule, Multimodal, [18F]-PET and Fluorescence Imaging Agent Targeting Prostate-Specific Membrane Antigen: First-in-Human Study. Clin. Genitourin. Cancer. 2021, 19, 405–416. [Google Scholar] [CrossRef]
- De Valk, K.S.; Deken, M.M.; Schaap, D.P.; Meijer, R.P.; Boogerd, L.S.; Hoogstins, C.E.; van der Valk, M.J.; Kamerling, I.M.; Bhairosingh, S.S.; Framery, B.; et al. Dose-Finding Study of a CEA-Targeting Agent, SGM-101, for Intraoperative Fluorescence Imaging of Colorectal Cancer. Ann. Surg. Oncol. 2021, 28, 1832–1844. [Google Scholar] [CrossRef]
- Krishnan, G.; van den Berg, N.S.; Nishio, N.; Juniper, G.; Pei, J.E.; Zhou, Q.; Lu, G.; Lee, Y.-J.; Ramos, K.; Iagaru, A.H.; et al. Metastatic and sentinel lymph node mapping using intravenously delivered Panitumumab-IRDye800CW. Theranostics 2021, 11, 7188–7198. [Google Scholar] [CrossRef] [PubMed]
- Newton, A.D.; Predina, J.D.; Frenzel-Sulyok, L.G.; Low, P.S.; Singhal, S.; Roses, R.E. Intraoperative Molecular Imaging Utilizing a Folate Receptor-Targeted Near-Infrared Probe Can Identify Macroscopic Gastric Adenocarcinomas. Mol. Imaging Biol. 2021, 23, 11–17. [Google Scholar] [CrossRef] [PubMed]
- Vonk, J.; de Wit, J.G.; Voskuil, F.J.; Tang, Y.H.; Hooghiemstra, W.T.; Linssen, M.D.; Broek, E.v.D.; Doff, J.J.; de Visscher, S.A.; Schepman, K.P.; et al. Epidermal growth factor receptor targeted fluorescence molecular imaging for postoperative lymph node assessment in patients with oral cancer. J. Nucl. Med. 2021, 63, 672–678. [Google Scholar] [CrossRef] [PubMed]
- Armstrong, G.R.; Khot, M.I.; Portal, C.; West, N.P.; Perry, S.L.; Maisey, T.I.; Tiernan, J.P.; Hughes, T.A.; Tolan, D.J.; Jayne, D.G. A novel fluorescent c-met targeted imaging agent for intra-operative colonic tumour mapping: Translation from the laboratory into a clinical trial. Surg. Oncol. 2022, 40, 101679. [Google Scholar] [CrossRef]
- De Gooyer, J.M.; Elekonawo, F.M.K.; Bremers, A.J.A.; Boerman, O.C.; Aarntzen, E.; de Reuver, P.R.; Nagtegaal, I.D.; Rijpkema, M.; de Wilt, J.H.W. Multimodal CEA-targeted fluorescence and radioguided cytoreductive surgery for peritoneal metastases of colorectal origin. Nat. Commun. 2022, 13, 2621. [Google Scholar] [CrossRef]
- Jonker, P.K.C.; Metman, M.J.H.; Sondorp, L.H.J.; Sywak, M.S.; Gill, A.J.; Jansen, L.; Links, T.P.; van Diest, P.J.; van Ginhoven, T.M.; Löwik, C.W.G.M.; et al. Intraoperative MET-receptor targeted fluorescent imaging and spectroscopy for lymph node detection in papillary thyroid cancer: Novel diagnostic tools for more selective central lymph node compartment dissection. Eur. J. Nucl. Med. Mol. Imaging 2022, 49, 3557–3570. [Google Scholar] [CrossRef] [PubMed]
- Nguyen, H.G.; van den Berg, N.S.; Antaris, A.L.; Xue, L.; Greenberg, S.; Rosenthal, J.W.; Muchnik, A.; Klaassen, A.; Simko, J.P.; Dutta, S.; et al. First-in-human Evaluation of a Prostate-specific Membrane Antigen-targeted Near-infrared Fluorescent Small Molecule for Fluorescence-based Identification of Prostate Cancer in Patients with High-risk Prostate Cancer Undergoing Robotic-assisted Prostatectomy. Eur. Urol. Oncol. 2023, 7, 63–72. [Google Scholar] [CrossRef]
- Stibbe, J.A.; de Barros, H.A.; Linders, D.G.J.; Bhairosingh, S.S.; Bekers, E.M.; van Leeuwen, P.J.; Low, P.S.; A Kularatne, S.; Vahrmeijer, A.L.; Burggraaf, J.; et al. First-in-patient study of OTL78 for intraoperative fluorescence imaging of prostate-specific membrane antigen-positive prostate cancer: A single-arm, phase 2a, feasibility trial. Lancet Oncol. 2023, 24, 457–467. [Google Scholar] [CrossRef]
- Meijer, R.P.J.; Galema, H.A.; Faber, R.A.; Bijlstra, O.D.; Maat, A.; Cailler, F.; Braun, J.; Keereweer, S.; Hilling, D.E.; Burggraaf, J.; et al. Intraoperative molecular imaging of colorectal lung metastases with SGM-101: A feasibility study. Eur. J. Nucl. Med. Mol. Imaging 2023, 51, 2970–2979. [Google Scholar] [CrossRef]
- Lauwerends, L.J.; van Driel, P.; Baatenburg de Jong, R.J.; Hardillo, J.A.U.; Koljenovic, S.; Puppels, G.; Mezzanotte, L.; Löwik, C.W.G.M.; Rosenthal, E.L.; Vahrmeijer, A.L.; et al. Real-time fluorescence imaging in intraoperative decision making for cancer surgery. Lancet Oncol. 2021, 22, e186–e195. [Google Scholar] [CrossRef]
- Azargoshasb, S.; Boekestijn, I.; Roestenberg, M.; KleinJan, G.H.; van der Hage, J.A.; van der Poel, H.G.; Rietbergen, D.D.D.; van Oosterom, M.N.; van Leeuwen, F.W.B. Quantifying the Impact of Signal-to-background Ratios on Surgical Discrimination of Fluorescent Lesions. Mol. Imaging Biol. 2023, 25, 180–189. [Google Scholar] [CrossRef] [PubMed]
- Warram, J.M.; de Boer, E.; van Dam, G.M.; Moore, L.S.; Bevans, S.L.; Walsh, E.M.; Young, E.S.; Carroll, W.R.; Stevens, T.M.; Rosenthal, E.L. Fluorescence imaging to localize head and neck squamous cell carcinoma for enhanced pathological assessment. J. Pathol. Clin. Res. 2016, 2, 104–112. [Google Scholar] [CrossRef]
- Wreesmann, V.B.; Katabi, N.; Palmer, F.L.; Montero, P.H.; Migliacci, J.C.; Gönen, M.; Carlson, D.; Ganly, I.; Shah, J.P.; Ghossein, R.; et al. Influence of extracapsular nodal spread extent on prognosis of oral squamous cell carcinoma. Head Neck 2016, 38 (Suppl. 1), E1192–E1199. [Google Scholar] [CrossRef] [PubMed]
- Stoffels, I.; Morscher, S.; Helfrich, I.; Hillen, U.; Leyh, J.; Burton, N.C.; Sardella, T.C.P.; Claussen, J.; Poeppel, T.D.; Bachmann, H.S.; et al. Metastatic status of sentinel lymph nodes in melanoma determined noninvasively with multispectral optoacoustic imaging. Sci. Transl. Med. 2015, 7, 317ra199. [Google Scholar] [CrossRef] [PubMed]
- Vonk, J.; Kukacka, J.; Steinkamp, P.J.; de Wit, J.G.; Voskuil, F.J.; Hooghiemstra, W.T.R.; Bader, M.; Jüstel, D.; Ntziachristos, V.; van Dam, G.; et al. Multispectral optoacoustic tomography for in vivo detection of lymph node metastases in oral cancer patients using an EGFR-targeted contrast agent and intrinsic tissue contrast: A proof-of-concept study. Photoacoustics 2022, 26, 100362. [Google Scholar] [CrossRef]
- Pal, R.; Lwin, T.M.; Krishnamoorthy, M.; Collins, H.R.; Chan, C.D.; Prilutskiy, A.; Nasrallah, M.P.; Dijkhuis, T.H.; Shukla, S.; Kendall, A.L.; et al. Fluorescence lifetime of injected indocyanine green as a universal marker of solid tumours in patients. Nat. Biomed. Eng. 2023, 7, 1649–1666. [Google Scholar] [CrossRef]
- Valdes, P.A.; Angelo, J.P.; Choi, H.S.; Gioux, S. qF-SSOP: Real-time optical property corrected fluorescence imaging. Biomed. Opt. Express 2017, 8, 3597–3605. [Google Scholar] [CrossRef]
Study | Reference | Target | Tracer | Target Tissue | Clinical Trial Design | Patients (n) | Harvested Lymph Nodes (n) | Used Fluorescence Camera System(s) | Intended Clinical Application | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Boogerd et al., 2018 | [21] | Carcinoembryonic antigen | SGM-101 | Colorectal cancer | Type E | 26 | N.S. | - Quest Artemis and Spectrum imaging system - PEARL imaging system | Intraoperative tumor and metastases detection | ||||
De Valk et al., 2021 | [31] | Carcinoembryonic antigen | SGM-101 | Colorectal cancer | Type E | 37 | 11 (all doses) | Quest Spectrum Imager | Intraoperative tumor and metastases detection (focusing on change in treatment strategy) | 83 * (in vivo/ex vivo) | 60 * (in vivo/ex vivo) | 71 * (in vivo/ex vivo) | 75 * (in vivo/ex vivo) |
De Gooyer et al., 2022 | [36] | Carcinoembryonic antigen | [111In]In-DOTA-labetuzumab- IRDye800CW | Metastasized colorectal cancer | Type E | 15 | N.S. | Quest Spectrum Imager | Intraoperative tumor and metastases detection | ||||
Meijer et al., 2023 | [40] | Carcinoembryonic antigen | SGM-101 | Colorectal lung metastases | Type E | 13 | 8 | - Quest Spectrum Imager - PEARL imaging system | Intraoperative metastases detection | ||||
Armstrong et al., 2022 | [35] | c-MET | EMI-137 | Colon cancer | Type C | 9 | 15 | Karl Storz laparoscopic camera system | Intraoperative tumor and metastases detection | ||||
Jonker et al., 2022 | [37] | c-MET | EMI-137 | Papillary thyroid cancer | Type C | 19 | 289 | IVIS spectrum imaging | Intraoperative lymph node metastases detection | 88 ** (ex vivo) | 26 ** (ex vivo) | N.S. ** (ex vivo) | 83 ** (ex vivo) |
Rosenthal et al., 2017 | [18] | Epidermal growth factor receptor | Cetuximab-IRDYe800CW | Head-and neck cancer | Type C | 12 | 471 | - Luna Imaging System - PEARL imaging system | Intraoperative lymph node metastases detection | 97 (ex vivo) | 93 (ex vivo) | 51 (ex vivo) | 100 (ex vivo) |
Tummers et al., 2018 | [22] | Epidermal growth factor receptor | Cetuximab-IRDye800 | Pancreatic ductal adenocarcinoma | Type E | 7 | 107 | - Laparoscopic PINPOINT 9000 system - Wide-field SurgVision Explorer - PEARL imaging system | Intraoperative tumor and lymph node metastases detection | ||||
Nishio et al., 2019 | [24] | Epidermal growth factor receptor | Panitumumab-IRDye800CW | Head-and neck cancer | Type C | 24 | 1012 | - Spy-Phi camera and IR9000 optical imaging platform - PEARL imaging system | Postoperative lymph node metastases detection before pathological examination | 94 (FFPE) | 85 (FFPE) | 36 (FFPE) | 99 (FFPE) |
Tummers et al., 2019 | [26] | Epidermal growth factor receptor | Cetuximab-IRDYe800CW | Pancreatic cancer | Type C | 7 | 72 (low-dose cohort) | - Wide-field SurgVision Explorer - PEARL imaging system | Intraoperative lymph node metastases detection | 100 (ex vivo) 91 (FFPE) | 78 (ex vivo) 66 (FFPE) | 36 * (ex vivo) N.S. (FFPE) | 100 * (ex vivo) N.S. (FFPE) |
Lu et al., 2020 | [29] | Epidermal growth factor receptor | Panitumumab-IRDYe800CW | Pancreatic cancer | Type C | 11 | 132 | - Laparoscopic PINPOINT 9000 system - Spy-Phi camera system - Wide-field SurgVision Explorer - PEARL imaging system - IGP-ELVIS imaging system | Intraoperative tumor and metastases detection | 70 (FFPE) | 91 * (FFPE) | 62 (FFPE) | 93 (FFPE) |
Krishnan et al., 2021 | [32] | Epidermal growth factor receptor | Panitumumab-IRDYe800CW | Head-and neck cancer | Type C | 27 | 581 (cN0 cohort) | - Spy-Phi camera and IR9000 optical imaging platform - PEARL imaging system | Intraoperative (sentinel) lymph node metastases detection | 100 (ex vivo) | 86 (ex vivo) | 100 * (ex vivo) | 100 (ex vivo) |
Vonk et al., 2021 | [34] | Epidermal growth factor receptor | Cetuximab-IRDYe800CW | Oral cancer | Type B | 22 | 514 | PEARL imaging system | Postoperative lymph node metastases detection before pathological examination | 100 (FFPE) | 87 (FFPE) | 49 (FFPE) | 100 (FFPE) |
Tummers et al., 2016 | [16] | Folate receptor | EC17 | Ovarian cancer and breast cancer | Type E | 15 | N.S. | Quest Artemis imaging system | Intraoperative tumor and metastases detection | ||||
Hoogstins et al., 2016 | [15] | Folate receptor | OTL38 | Ovarian cancer | Type E | 12 | 13 | Quest Artemis imaging system | Intraoperative tumor and metastases detection | ||||
Boogerd et al., 2018 | [20] | Folate receptor | OTL38 | Endometrial cancer | Type E | 4 | 66 | Quest Artemis imaging system | Intraoperative tumor and metastases detection | 100 (in vivo) | 70 (in vivo) | 48 (in vivo) | 100 (in vivo) |
Hoogstins et al., 2019 | [23] | Folate receptor | OTL38 | Ovarian cancer | Type E | 6 | 38 | Quest Artemis imaging system | Intraoperative metastases detection | ||||
Randall et al., 2019 | [25] | Folate receptor | OTL38 | Ovarian cancer | Type E | 48 | N.S. | - Quest Artemis imaging system - Novadaq PINPOINT LI system - Visionsense VS3 imaging system | Intraoperative tumor and metastases detection | ||||
Newton et al., 2021 | [33] | Folate receptor | OTL38 | Gastric cancer | Type E | 5 | N.S. | Visionsense VS3 Iridium imaging system | Intraoperative tumor and metastases detection | ||||
De Valk et al., 2020 | [28] | Integrins (associated with tumor angiogenesis) | cRGD-ZW800-1 | Colon cancer | Type B | 12 | 209 | - Olympus Visera Elite I - Quest Spectrum Imager - PEARL imaging system | Intraoperative tumor and metastases detection | 100 (ex vivo) | 87 (ex vivo) | 33 (ex vivo) | 100 (ex vivo) |
Unkart et al., 2017 | [19] | Matrix metalloproteinases | AVB-620 | Breast cancer | Type C | 26 | N.S. | N.S. | Intraoperative tumor and lymph node metastases detection | ||||
Aras et al., 2021 | [30] | Prostate-specific membrane antigen | [18 F]-BF3- Cy3-ACUPA | Prostate cancer | Type B | 10 | N.S. | Custom made | Intraoperative tumor and metastases detection | ||||
Stibbe et al., 2023 | [39] | Prostate-specific membrane antigen | OTL78 | Prostate cancer | Type E | 18 | 20 (optimal dose cohort) | - Da Vinci Si or Xi Surgical System - VisionSense near-infrared imaging system | Intraoperative tumor and metastases detection | 0 (in vivo, ex vivo) 100 (FFPE) 100 (microscopy) | 100 (in vivo, ex vivo) 100 (FFPE) N.S. (microscopy) | N.S. (in vivo, ex vivo) 100 (FFPE) 100 (microscopy) | 90 (in vivo, ex vivo) 100 (FFPE) N.S. (microscopy) |
Nguyen et al., 2023 | [38] | Prostate-specific membrane antigen | IS-002 | Prostate cancer | Type D | 24 | 309 (all doses) | - Da Vinci Si or Xi Surgical System | Intraoperative tumor and metastases detection | 57 * (in vivo) | 73 * (in vivo) | 9 (in vivo) | 97 (in vivo) |
Lamberts et al., 2017 | [17] | Vascular endothelial growth factor | Bevacizumab-IRDye800CW | Breast cancer | Type E | 20 | N.S. | Custom made (Technical University Munich) | Intraoperative tumor and metastases detection | ||||
De Jongh, et al., 2020 | [27] | Vascular endothelial growth factor | Bevacizumab-800CW | Locally advanced rectal cancer | Type B | 17 | N.S. | Wide-field SurgVision Explorer | Intraoperative tumor (focusing on margins) and metastases detection |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zweedijk, B.E.; Dalmeijer, S.W.R.; van Manen, L.; Galema, H.A.; Lauwerends, L.J.; Abbasi, H.; Kremer, B.; Verhoef, C.; Robinson, D.J.; Koppes, S.A.; et al. Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review. Cancers 2025, 17, 1352. https://doi.org/10.3390/cancers17081352
Zweedijk BE, Dalmeijer SWR, van Manen L, Galema HA, Lauwerends LJ, Abbasi H, Kremer B, Verhoef C, Robinson DJ, Koppes SA, et al. Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review. Cancers. 2025; 17(8):1352. https://doi.org/10.3390/cancers17081352
Chicago/Turabian StyleZweedijk, Bo E., Sebastiaan W. R. Dalmeijer, Labrinus van Manen, Hidde A. Galema, Lorraine J. Lauwerends, Hamed Abbasi, Bernd Kremer, Cornelis Verhoef, Dominic J. Robinson, Sjors A. Koppes, and et al. 2025. "Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review" Cancers 17, no. 8: 1352. https://doi.org/10.3390/cancers17081352
APA StyleZweedijk, B. E., Dalmeijer, S. W. R., van Manen, L., Galema, H. A., Lauwerends, L. J., Abbasi, H., Kremer, B., Verhoef, C., Robinson, D. J., Koppes, S. A., Vahrmeijer, A. L., van der Vorst, J. R., Hilling, D. E., & Keereweer, S. (2025). Molecular-Targeted Fluorescence Lymph Node Imaging Could Play a Clinical Role in the Surgical Setting: A Systematic Review. Cancers, 17(8), 1352. https://doi.org/10.3390/cancers17081352