Virtual biopsy
Imaging method helps doctors detect disease without tissue samples
Stanford Medicine researchers have developed a technique for conducting a “virtual biopsy.” The researchers use lasers to harmlessly penetrate tissue and create a high-resolution, 3D reconstruction of the cells it contains. Then they make cross-sectional images that mimic those generated by a standard biopsy, in which a sample of tissue is sliced into thin layers and placed on a slide to be examined under a microscope.
The technique, described in a paper published in April in Science Advances, could be used to noninvasively scan the skin for unhealthy cells as well as provide rapid results on tissue biopsied conventionally. It could also reveal more information than do commonly used diagnostic approaches.
“We’ve not only created something that can replace the current gold-standard pathology slides for diagnosing many conditions, but we actually improved the resolution of these scans so much that we start to pick up information that would be extremely hard to see otherwise,” said Adam de la Zerda, PhD, an associate professor of structural biology and the senior author of the paper.
The method was developed by Yonatan Winetraub, PhD, a former graduate student in the de la Zerda lab who now leads his own Stanford Medicine research lab.
In a traditional biopsy, tissue is sent to a pathologist, who slices it into thin layers. The pathologist then stains each layer with chemicals called hematoxylin and eosin (H&E), which makes cell patterns, shapes and structures easier to see. These slides are routinely used for diagnosing cancers and other diseases, but making them is labor intensive.
De la Zerda and Winetraub enhanced optical coherence tomography, which is typically used by ophthalmologists to image the back of the eye, so it would work in other organs. (OCT scans measure how light waves from a laser bounce off a tissue to create a rendering of its insides.)
“We kept improving and improving the quality of the image, letting us see smaller and smaller details of a tissue,” de la Zerda said. “And we realized the OCT images we were creating were really getting very similar to the H&Es in terms of what they could show.”
De la Zerda and his colleagues thought clinicians would be more apt to use OCT if the images looked familiar. So Winetraub turned to artificial intelligence to help convert the scans into flat images resembling H&E slides.
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