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How your phone's camera could help detect a rare cancer in kids.

What wasn't available for his son may now save other kids.

How your phone's camera could help detect a rare cancer in kids.
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In 2008, 1-year-old Noah Shaw was diagnosed with a rare form of eye cancer called retinoblastoma.

By the time he received the diagnosis, the cancer had progressed and the treatment plan was extremely intense.

Months of chemo and radiation followed, and Noah had to undergo surgery to remove his right eye to keep the cancer from spreading to his brain.


All images from Bryan Shaw, used with permission.

That's a lot to go through in your first year of life.

As worried parents often do, Bryan and Elizabeth Shaw wondered if there were any missing warning signs that would have helped get Noah's diagnosis sooner.

They remembered the photographs that first raised concerns. Instead of the usual red dot of a pupil, they had noticed one of Noah's eyes appeared different from the other.

Being a scientist himself, Bryan wanted to see if he could track down when that difference first appeared. Bryan and Elizabeth turned to Noah's baby pictures to see how early this symptom showed up in photos before he was diagnosed.

Lo and behold, a clear warning sign is exactly what they found.

It's all about a white reflection that appears in the eye in photos with a camera flash.

Blood vessels in the back of the eye will normally reflect red, but if there is a tumor or other issue present, the eye may appear differently.

For Noah, that white glow first began appearing in photos when he was just 12 days old.

The presence of a white glow in a child's eye can help determine whether a baby has leukocoria, an early indicator of an eye problem ranging from a refractive error, where a baby needs glasses, to a rare form of cancer, like in Noah's case.

Noah, now a lively 7-year-old, is doing great. But Bryan never stopped thinking about how he could help other kids detect their eye problems earlier on.

"If I would have had some software in it telling me, 'Hey, go get this checked out,' that would have sped up my son's diagnosis and the tumors would have been just a little bit smaller when we got to them. There might have been fewer," Bryan told NPR.

A chemist at the University of Baylor, Bryan decided to shake up his career path by exploring life as a software designer too.

Bryan launched a free app called CRADLE that screens kids for leukocoria through their photos.

Created with the help of Baylor colleagues and graduate students, the app is available on both iPhone and Android for free under the name CRADLE, which stands for ComputeR Assisted Detector of LEukocoria. Clever.

The app can search your device for all photos that might contain white eye, given that leukocoria can show up inconsistently. It can also be used in real-time, snapping a photo through the app itself.

Even better? The app is working.

If the app finds a photo that could be a leukocoria, it recommends a visit straight to the pediatrician.

"Multiple families have used it to catch cancer in their children at such early stages — way before doctors — that the children received only laser treatment, no chemo, no radiation, no eye removal," Bryan said in an email to Welcometoterranova.

And while retinoblastoma itself is very rare — fewer than 12 out of 1 million children aged 0-4 will develop it — the app goes beyond to help with other eye problems.

Shaw says "white eye" in kids is a symptom of a lot more than cancer. The app has caught Coats' disease, myelinated retinal nerve fiber layer, and a bunch of refractive errors (i.e., kids needing glasses).

Posting and sharing photos is more than just a great way to connect and document life: It can now share valuable information about the health of a child's eyes.

Bryan knows early diagnosis is key and parents see their kids a lot more than doctors do. While it's no substitute for being seen by an actual doctor, there is no question that this app can make a difference.

"From here, the software is going to get better," he told People. "It's going to get more accurate as we collect more and more pictures to train it and make it smarter."

Keep the pictures comin'.

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