Development of preclinical ultrasound imaging techniques to identify and image sentinel lymph nodes in a cancerous animal model

Bacou, Marion and Rajasekaran, Vidya and Thomson, Adrian and Sjöstrand, Sandra and Kaczmarek, Katarzyna and Ochocka-Fox, Anna Maria and Gerrard, Adam D. and Moug, Susan and Jansson, Tomas and Mulvana, Helen and Moran, Carmel M. and Farrington, Susan M. (2022) Development of preclinical ultrasound imaging techniques to identify and image sentinel lymph nodes in a cancerous animal model. Cancers, 14 (3). 561. ISSN 2072-6694 (https://doi.org/10.3390/cancers14030561)

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Abstract

Lymph nodes (LNs) are believed to be the first organs targeted by colorectal cancer cells detached from a primary solid tumor because of their role in draining interstitial fluids. Better detection and assessment of these organs have the potential to help clinicians in stratification and designing optimal design of oncological treatments for each patient. Whilst highly valuable for the detection of primary tumors, CT and MRI remain limited for the characterization of LNs. B-mode ultrasound (US) and contrast-enhanced ultrasound (CEUS) can improve the detection of LNs and could provide critical complementary information to MRI and CT scans; however, the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) guidelines advise that further evidence is required before US or CEUS can be recommended for clinical use. Moreover, knowledge of the lymphatic system and LNs is relatively limited, especially in preclinical models. In this pilot study, we have created a mouse model of metastatic cancer and utilized 3D high-frequency ultrasound to assess the volume, shape, and absence of hilum, along with CEUS to assess the flow dynamics of tumor-free and tumor-bearing LNs in vivo. The aforementioned parameters were used to create a scoring system to predict the likelihood of a disease-involved LN before establishing post-mortem diagnosis with histopathology. Preliminary results suggest that a sum score of parameters may provide a more accurate diagnosis than the LN size, the single parameter currently used to predict the involvement of an LN in disease.

ORCID iDs

Bacou, Marion, Rajasekaran, Vidya, Thomson, Adrian, Sjöstrand, Sandra, Kaczmarek, Katarzyna ORCID logoORCID: https://orcid.org/0000-0002-3193-0070, Ochocka-Fox, Anna Maria, Gerrard, Adam D., Moug, Susan, Jansson, Tomas, Mulvana, Helen ORCID logoORCID: https://orcid.org/0000-0002-5058-0299, Moran, Carmel M. and Farrington, Susan M.;
CORE (COnnecting REpositories)