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Excelitas Technologies Corp. - X-Cite Vitae LB 11/24

Bioimaging Technique Isolates Moving Tissue

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Light-guiding technology could take scientists on a journey inside blood vessels.

The new technology — time-reversed adapted-perturbation (TRAP) optical focusing, developed by a team at Washington University in St. Louis — guides light into tissue to seek movement, such as blood flow, that is obscured by highly scattering media. This light appears differently than light that passes through stationary tissue.

The researchers demonstrated that light passing through stationary tissue can be subtracted, leaving only the scattered light caused by motion. That light can then be sent to its original source via time reversal, showing that “it is possible to focus light to the origin of the perturbation,” the researchers wrote in their study.

“This can potentially be used in imaging or therapy,” said professor Dr. Lihong Wang, recent recipient of SPIE’s 2015 Britton Chance Biomedical Optics Award. “For example, focusing pulsed light on port wine stains, which are excessive growth of blood vessels, could remove the stains without damaging the surrounding normal skin.”

With existing optical imaging technology, it is possible to see about 1 mm into the body. Other methods used to help light penetrate deeper have required implanted or virtual guide stars, which can be invasive and inconvenient.

The focusing TRAP provides can enhance contrast by redistributing and concentrating light on many targets, allowing images to be taken at greater depths.

Potential applications include imaging and photoablation of angiogenic vessels in tumors.

The work was funded by the National Institutes of Health. The research was published in Nature Photonics (doi: 10.1038/nphoton.2014.251). 

For more information, visit www.wustl.edu.
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Published: November 2014
Research & TechnologyImagingOpticsBiophotonicsAmericasbiomedical engineeringWashington University in St. LouisSchool of Engineering & Applied Sciencetime-reversed adapted-perturbation optical focusingTRAP.Lihong WangBioScan

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