Skin cancer diagnosis is about to undergo a revolution
Patternox is developing an optical scanner to detect suspicious light patterns in lesions long before changes can be seen on the skin’s surface.
When Ofir Aharon was finishing his PhD in electro-optics engineering, his mother was diagnosed with melanoma, a serious form of skin cancer.
He decided to channel his knowledge into inventing a potentially lifesaving device that could detect unique patterns of light movements in the skin before visible signs such as changes in pigmentation show up on the surface.
“Physicians say 50 percent of skin cancer starts out ‘innocent’ and then becomes cancer, but pathologists familiar with tissue structure say 95% of lesions that look innocent already started as cancer. I wondered why there was no tool that could show the early deterioration of lesions well before they became pigmented,” Aharon tells ISRAEL21c.
Aharon’s revolutionary discovery is that the movement of light scattering back to the imaging camera from a cancerous lesion looks much different than from a benign lesion.
Having filed a US patent application in early 2020, Patternox will launch a seed round in July with hopes of having PatScope FDA approved and commercialized in about two years.
Aharon envisions a unique artificial intelligence (AI) system and reimbursement strategy so patients will be able to perform the scan at home with virtual assistance from their dermatologist.
‘Something we’ve never looked at before’
Florida-based dermatologist Dr. Barry Galitzer is performing clinical trials using a PatScope prototype.
Dr. Barry Galitzer of the Skin Center in Florida testing the PatScope. Photo courtesy of Dr. Barry Galitzer
“About a year ago, I read an article about Ofir’s technology to test for melanoma in advance, and I contacted him because I was excited about this,” Galitzer tells ISRAEL21c. “It’s a new concept enabling us to see something we’ve never looked at before.”
Since December 2020, Galitzer has built a database of almost 200 scanned images. Each lesion is then biopsied and studied under a microscope to compare histological findings with the PatScope scans.
The more he uses the scanner the more easily he can discern what he is seeing, Galitzer says. Once there’s a large enough sample database to learn from, AI could interpret the scanned images.
“That is the exciting part,” he says. “AI would be incredible in giving us the answers we need.”
This technology could reduce unnecessary biopsies, Galitzer adds.
“We could evaluate the spot and immediately see if it has signs of abnormality and then take a biopsy to confirm that suspicion.”