Published in

MDPI, Biomedicines, 7(10), p. 1610, 2022

DOI: 10.3390/biomedicines10071610

Links

Tools

Export citation

Search in Google Scholar

Non-Invasive Imaging and Scoring of Peritoneal Metastases in Small Preclinical Animal Models Using Ultrasound: A Preliminary Trial

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Background: The peritoneum is a common site for the formation of metastases originating from several gastrointestinal and gynecological malignancies. A representative preclinical model to thoroughly explore the pathophysiological mechanisms and to study new treatment strategies is important. A major challenge for such models is defining and quantifying the (total) tumor burden in the peritoneal cavity prior to treatment, since it is preferable to use non-invasive methods. We evaluated ultrasound as a simple and easy-to-handle imaging method for this purpose. Methods: Peritoneal metastases were established in six WAG/Rij rats through i.p. injections of the colon carcinoma cell line CC-531. Using ultrasound, the location, number and size of intraperitoneal tumor nodules were determined by two independent observers. Tumor outgrowth was followed using ultrasound until the peritoneal cancer index (PCI) was ≥8. Interobserver variability and ex vivo correlation were assessed. Results: Visible peritoneal tumor nodules were formed in six WAG/Rij rats within 2–4 weeks after cell injection. In most animals, tumor nodules reached a size of 4–6 mm within 3–4 weeks, with total PCI scores ranging from 10–20. The predicted PCI scores using ultrasound ranged from 11–19 and from 8–18, for observer 1 and 2, respectively, which was quite similar to the ex vivo scores. Conclusions: Ultrasound is a reliable non-invasive method to detect intraperitoneal tumor nodules and quantify tumor outgrowth in a rat model.