Accurate detection and characterization of sentinel lymph nodes (SLNs) that receive drainage from a primary cancer (e.g., breast or melanoma) have a direct impact on patient management. Two methods are currently used to identify SLNs;peritumoral injection of radioisotopes followed by scintigraphy and injection of dye with detection of dye-stained SLNs at surgery. However, each of these methods has potential limitations that can adversely impact the detection of SLNs and the accuracy of disease staging. Furthermore, isotope imaging requires ionizing radiation, blue dye can cause anaphylactic reactions and neither of these techniques provides an accurate noninvasive depiction of lymphatic anatomy. Our group has demonstrated that contrast-enhanced ultrasound imaging (CEUS) after subdermal administration of a tissue-specific ultrasound contrast agent (UCA), can be used to noninvasively map lymphatic drainage and localize SLNs (so called """"""""lymphosonography""""""""). Our NIH funded investigations using a swine model with naturally occurring melanomas have confirmed that CEUS is superior to radioisotope imaging detecting almost 20 % more SLNs. However, the ability of lymphosonography to characterize SLNs as malignant or benign was slightly worse than that of standard grayscale ultrasound (80 % vs. 86 %, respectively). The specificity of CEUS improves with the use of a targeted UCA, in which targeting ligands are attached to the surface of the agent to improve affinity. Hence, the current proposal will expand on the concept of lymphosonography by including a triple-targeted molecular UCA to improve SLN characterization. We hypothesize that subdermal lymphosonogray followed by intravenous (IV) injection of a triple-targeted UCA (targeted to avb3 integrin, P-selectin and VEGFR2) will permit superior detection of SLNs as well as accurate characterization as benign or metastatic. Following an in vitro validation study, 20 melanoma-bearing swine with around 125 SLNs will be studied. An RES-specific UCA will be injected around each melanoma to permit detection of the SLNs. Then the triple-targeted UCA (i.e., molecular lymphosonography) will be injected IV and the presence or absence of metastatic deposits will be determined. Finally, blue dye will be injected around the melanoma and a surgeon will resect the dye-stained SLNs, which will be submitted to pathology to determine if they contain metastases. The accuracy of tumor detection in the SLNs identified by molecular lymphosonography will be compared to that of standard CEUS (i.e., using a non-targeted UCA) with pathology as the reference standard. The potential benefits of this innovative study will be the development of a minimally-invasive imaging method (molecular lymphosonography) to identify SLNs and accurately diagnose metastatic SLN involvement, thereby significantly reducing the need to perform excisional lymph node biopsies, reducing procedure-related complications and improving patient outcome.

Public Health Relevance

Preoperative diagnosis of tumor involvement of regional lymph nodes is critical for surgical management in patients with cancers. A specific ultrasound contrast agent will be administered around melanoma tumors in swine model to detect these lymph nodes and followed by IV injection of another contrast agent targeted to the identified nodes to detect metastases within the lymph nodes. The long-term benefits of this study will be the development of a minimally-invasive, safe, diagnostic imaging method to precisely localize and characterize lymph nodes, thereby obviating, or significantly reducing, the need to perform radical lymph node resections and improving patient outcomes.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZCA1-SRLB-J (J3))
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Henderson, Lori A
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Thomas Jefferson University
Schools of Medicine
United States
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Nam, Kibo; Stanczak, Maria; Forsberg, Flemming et al. (2017) Sentinel Lymph Node Characterization with a Dual-Targeted Molecular Ultrasound Contrast Agent. Mol Imaging Biol :