Sentinel Lymph Node Characterization with a Dual-Targeted Molecular Ultrasound Contrast Agent.
Publication/Presentation Date
4-1-2018
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 α
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 α
Volume
20
Issue
2
First Page
221
Last Page
229
ISSN
1860-2002
Published In/Presented At
Nam, K., Stanczak, M., Forsberg, F., Liu, J. B., Eisenbrey, J. R., Solomides, C. C., & Lyshchik, A. (2018). Sentinel Lymph Node Characterization with a Dual-Targeted Molecular Ultrasound Contrast Agent. Molecular imaging and biology, 20(2), 221–229. https://doi.org/10.1007/s11307-017-1109-3
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
28762204
Department(s)
Administration and Leadership
Document Type
Article