Improved detection of pancreatic islets in vivo using double contrast
Related Experiment Video
Updated: May 30, 2026
Stabilized Longitudinal In Vivo Cellular-Level Visualization of the Pancreas in a Murine Model with a Pancreatic Intravital Imaging Window
Published on: May 6, 2021
Vít Herynek1, Zuzana Berková, Eva Dovolilová
1MR-Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic. vit.herynek@medicon.cz
The transplantation of pancreatic islets containing β-cells, which produce insulin, is an alternative approach to the treatment of type 1 diabetes mellitus. The non-invasive visualization of transplanted islets can be performed using MRI; however, this requires labeling of the islets with a suitable contrast agent prior to transplantation. The detection of islets labeled by iron oxide-based contrast agents and transplanted into the liver tissue can be significantly improved using the intravenous administration of a suitable gadolinium contrast agent prior to MRI. The applied contrast agent not only improves the contrast-to-noise ratio, but also eliminates artifacts that may lead to an overestimation of the number of hypointense spots and their area; thus it improves the accuracy of automated and semi-automated procedures used for transplanted islet segmentation and quantification.
The transplantation of pancreatic islets containing β-cells, which produce insulin, is an alternative approach to the treatment of type 1 diabetes mellitus. The non-invasive visualization of transplanted islets can be performed using MRI; however, this requires labeling of the islets with a suitable contrast agent prior to transplantation. The detection of islets labeled by iron oxide-based contrast agents and transplanted into the liver tissue can be significantly improved using the intravenous administration of a suitable gadolinium contrast agent prior to MRI. The applied contrast agent not only improves the contrast-to-noise ratio, but also eliminates artifacts that may lead to an overestimation of the number of hypointense spots and their area; thus it improves the accuracy of automated and semi-automated procedures used for transplanted islet segmentation and quantification.
