Probe goes below skin to flag lesions
U. ROCHESTER (US) — A new optical technology that takes high-resolution images under the skin’s surface may eliminate surgery to detect if lesions are benign or cancerous.
Instead, the tip of a roughly one-foot-long cylindrical probe is placed in contact with the tissue, and within seconds a clear, high-resolution, 3-D image of what lies below the surface emerges.
“My hope is that, in the future, this technology could remove significant inconvenience and expense from the process of skin lesion diagnosis,” says Jannick Rolland, professor of optical engineering and biomedical engineering at the University of Rochester.
“When a patient walks into a clinic with a suspicious mole, for instance, they wouldn’t have to have it necessarily surgically cut out of their skin or be forced to have a costly and time-consuming MRI done.
Instead, a relatively small, portable device could take an image that will assist in the classification of the lesion right in the doctor’s office.”
Rolland presented her findings at the American Association for the Advancement of Science’s 2011 annual meeting in Washington, D.C.
The device uses a unique liquid lens setup developed by Rolland for a process known as Optical Coherence Microscopy. In a liquid lens, a droplet of water takes the place of the glass in a standard lens.
As the electrical field around the water droplet changes, the droplet changes its shape and therefore changes the focus of the lens, allowing the device to take thousands of pictures focused at different depths below the skin’s surface.
Combining the images creates a fully in-focus image of all of the tissue up to 1 millimeter deep in human skin, including important skin tissue structures. Because the device uses near infrared light instead of ultrasounds, the images have a precise, micron-scale resolution instead of a millimeter-scale resolution.
The process has been successfully tested in in-vivo human skin and several papers on it have been published in peer-reviewed journals.
The next step is to start using it in a clinical research environment so its ability to discriminate between different types of lesions may be assessed.
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