Datasets may allow for 3D visualizations of pancreas to improve diabetes research

Researchers from Umea University in Sweden have developed datasets capable of mapping the distribution and volume of insulin-producing cells in the pancreas in 3D. The development of such technology could improve visual and quantitative information that may be used for future diabetes research.

The study, published in Scientific Data, was led by Ulf Ahlgren, a professor at Umea University who had previously developed methods creating 3D images of insulin cell distribution within the pancreas. The research team examined how the new dataset improves visualization of insulin-producing cells. These images were based on optical projection tomography (OPT), which is similar to medical x-rays but rely instead on regular light.

"We believe that the current publication represents the most comprehensive anatomical and quantitative description of the insulin cell distribution in the pancreas,” said Ahlgren. “By making these datasets accessible to other researchers, the data will be available for use as a powerful tool for a great number of diabetes studies. Examples may include planning of stereological analyses in the development of non-invasive imaging techniques or various types of computational modeling and statistical analyses.”

The datasets include information on individual pancreatic islets and their 3D coordinates, as well as the appearance of the entire pancreases in both healthy and obese mice. The study, published in Scientific Reports, was used to identify the changes in the islets. Using advanced visualization, researchers were able to pinpoint lesions in the pancreatic islets caused by internal bleeding due to increased blood flow and unstable blood vessels.

"Obese mice have been described in thousands of publications," said Ahlgren. "But the large prevalence of such internal islet lesions have never before been identified and visualized."