Molecular Imaging and Biology

, Volume 20, Issue 2, pp 221–229 | Cite as

Sentinel Lymph Node Characterization with a Dual-Targeted Molecular Ultrasound Contrast Agent

  • Kibo Nam
  • Maria Stanczak
  • Flemming Forsberg
  • Ji-Bin Liu
  • John R. Eisenbrey
  • Charalambos C. Solomides
  • Andrej Lyshchik
Research Article

Abstract

Purpose

The purpose of this study was to assess the performance of molecular ultrasound with dual-targeted microbubbles to detect metastatic disease in the sentinel lymph nodes (SLNs) in swine model of naturally occurring melanoma. The SLN is the first lymph node in the lymphatic chain draining primary tumor, and early detection of metastatic SLN involvement is critical in the appropriate management of melanoma.

Procedure

Nine Sinclair swine (weight 3–7 kg; Sinclair BioResources, Columbia, MO, USA) with naturally occurring melanoma were examined. Siemens S3000 scanner with a 9L4 probe was used for imaging (Siemens Healthineers, Mountain View, CA). Dual-targeted contrast agent was created using Targestar SA microbubbles (Targeson, San Diego, CA, USA) labeled with ανβ3-integrin and P-selectin antibodies. Targestar SA microbubbles labeled with IgG-labeled were used as control. First, peritumoral injection of Sonazoid contrast agent (GE Healthcare, Oslo, Norway) was performed to detect SLNs. After that, dual-targeted and IGG control Targestar SA microbubbles were injected intravenously with a 30-min interval between injections. Labeled Targestar SA microbubbles were allowed to circulate for 4 min to enable binding. After that, two sets of image clips were acquired several seconds before and after a high-power destruction sequence. The mean intensity difference pre- to post-bubble destruction within the region of interest placed over SLN was calculated as a relative measure of targeted microbubble contrast agent retention. This process was repeated for non-SLNs as controls. All lymph nodes evaluated on imaging were surgically removed and histologically examined for presence of metastatic involvement.

Results

A total of 43 lymph nodes (25 SLNs and 18 non-SLNs) were included in the analysis with 18 SLNs demonstrating metastatic involvement greater than 5 % on histology. All non-SLNs were benign. The mean intensity (± SD) of the dual-targeted microbubbles for metastatic SLNs was significantly higher than that of benign LNs (18.05 ± 19.11 vs. 3.30 ± 6.65 AU; p = 0.0008), while IgG-labeled control microbubbles demonstrated no difference in retained contrast intensity between metastatic and benign lymph nodes (0.39 ± 1.14 vs. 0.03 ± 0.24 AU; p = 0.14).

Conclusions

The results indicate that dual-targeted microbubbles labeled with P-selectin and ανβ3-integrin antibodies may aid in detecting metastatic involvement in SLNs of melanoma.

Key words

Sentinel lymph nodes Characterization Melanoma Metastasis Ultrasound Contrast imaging Targeted microbubbles Angiogenesis Inflammation 

Notes

Acknowledgements

Joseph Altemus, a lab animal veterinary technician in Thomas Jefferson University, is specifically acknowledged for help with animal care. This study was supported by NIH R21 CA185121 and GE Healthcare provided Sonazoid, while Siemens provided the S3000 HELX scanner. However, the authors had sole control of the data and information provided for publication.

Compliance with Ethical Standards

This study was approved by the Thomas Jefferson University Animal Care and Use Committee and was performed in accordance with the guidelines of the National Institutes of Health and supervised by our Laboratory Animal Services Department guidelines.

Conflict of Interest

Dr. Forsberg is on the Speaker’s Bureau of GE Healthcare, and Dr. Eisenbrey receives funding, equipment, and drug support from GE Healthcare. The other authors declare that they have no relevant conflict of interest.

Ethical Approval

All applicable institutional and/or national guidelines for the care and use of animals were followed.

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Copyright information

© World Molecular Imaging Society 2017

Authors and Affiliations

  • Kibo Nam
    • 1
  • Maria Stanczak
    • 1
  • Flemming Forsberg
    • 1
  • Ji-Bin Liu
    • 1
  • John R. Eisenbrey
    • 1
  • Charalambos C. Solomides
    • 2
  • Andrej Lyshchik
    • 1
  1. 1.Department of RadiologyThomas Jefferson UniversityPhiladelphiaUSA
  2. 2.Department of PathologyThomas Jefferson UniversityPhiladelphiaUSA

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