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  • Video: 3-D Imaging Platform Studies Cells in Action
Oct 2014
PHILADELPHIA, Oct. 7, 2014 — Software that uses video gaming gear is bringing live cells into a 3-D spotlight.

Researchers from Drexel University are developing a 3-D software program — Lineage Editing and Validation (LEVER 3-D) — to identify, tag and track live cells, as well as capture patterns of motion and cell division, using sequences of microscopic time-lapse images.

Such enhanced imaging produces a 3-D rendering of the cells.

In the study, LEVER 3-D, which compiles data from the multi-layered microscopic images, was run on a graphics- and gaming-optimized computer while the researchers used 3-D gaming glasses to look at the microscopic cross-section.

The process of tracking cell lineage over time typically requires biologists to watch the time-lapse images and note by hand when the cells multiply. This traditional method creates a graphic representation of cell division (lineage tree) over time, but is known to be a tedious, time-consuming process.

The LEVER software can delineate cells, color code them and denote the exact moment of their division, according to the researchers, adding that it has also proven more accurate and can provide more data than manual processing.

“LEVER 3-D … opens new vistas for understanding the stem cell niche,” said Dr. Sally Temple, a cell biologist at the Neural Stem Cell Institute in Rensselaer, N.Y., who has been using the new software as part of her stem cell research.

The Drexel researchers employed a stereo-vision projector to bring the 3-D image data to life, offering unique vantage points that are not possible when looking through a conventional microscope.

“It’s like Photoshop for cell biologists,” said Drexel professor Dr. Andrew Cohen. “The software outlines cells and blood vessels, keeping track of them as they’re dividing and moving around one another. This provides a wealth of information on the patterns of cell shape, motion and division. Visualization of the 3-D microscopy data together with the analysis results is a key step to measure and ultimately understand what drives these cells.”

The researchers’ goal is to enhance existing visual data to facilitate identification of cell changes over time. This information is key to studying the abnormal cell proliferation that causes cancer and also when using stem cells in regenerative medicine.

The work was funded by the National Institute on Aging. The research was published in BMC Bioinformatics (doi: 10.1186/1471-2105-15-328).

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