Developed by researchers at Rice University, a new AI microscope can rapidly image large sections of tissue to allow doctors to examine tumor margins in real-time.
Known as the DeepDOF, it uses deep learning AI technology to speed up image collection and processing which result in incredibly precise images. Furthermore, DeepDOF is the first microscope designed with coexisting imaging and image analysis.
Mary Jin, a PhD student in electrical and computer engineering at Rice University and co-lead author of the study in the Proceedings of the National Academy of Sciences, said: “The main goal of the surgery is to remove all the cancer cells, but the only way to know if you got everything is to look at the tumor under a microscope,”
“Today, you can only do that by first slicing the tissue into extremely thin sections and then imaging those sections separately, this slicing process requires expensive equipment and the subsequent imaging of multiple slices is time-consuming. Our project seeks to basically image large sections of tissue directly, without any slicing.” said Jin.
When it comes to tumor analysis, the normal ones require the sample to be prepared and sliced into exceedingly thin layers before being assessed under a microscope. It is accurate however, the process is too costly and time-consuming. DeepDOF on the other hand, uses a standard optical microscope in combination with an inexpensive optical phase mask and offers high-level imaging in as little as two minutes.
Coauthor Ann Gillenwater, a professor of head and neck surgery at the University of Texas MD Anderson, said: “Current methods to prepare tissue for margin status evaluation during surgery have not changed significantly since first introduced over 100 years ago,
“By bringing the ability to accurately assess margin status to more treatment sites, the DeepDOF has potential to improve outcomes for cancer patients treated with surgery.”
Credit: Brandon Martin/Rice