Artificial intelligence can accurately detect diabetic eye

High blood sugar can damage tiny blood vessels at the back of the eye. Sometimes, tiny bulges protrude from the blood vessels, leaking fluid and blood into the retina.

In a new advancement in science, researchers have found that an automated; artificial intelligence (AI) screening system is capable of accurately discovering diabetic retinopathy 95.5 per cent of the times.

Moreover, the system doesn't require inputs from an expert ophthalmologist and it can provide a reading in just 60 seconds.

Researchers presented these findings at AAO 2019, the 123rd Annual Meeting of the American Academy of Ophthalmology.

Diabetic retinopathy can develop over time in people with diabetes, especially when they have poor control over their blood sugar levels.

High blood sugar can damage tiny blood vessels at the back of the eye. Sometimes, tiny bulges protrude from the blood vessels, leaking fluid and blood into the retina.

This fluid can cause swelling or edema in an area of the retina that allows us to see clearly. At first, diabetic retinopathy may cause no symptoms or only mild vision problems. Eventually, it can cause blindness.

Ophthalmologists have effective treatments for diabetic retinopathy, but they work best when the condition detected early. That's why ophthalmologists recommend patients be screened every year.

A system called EyeArt has shown promise in earlier studies. It was used to screen 893 patients with diabetes at 15 different medical locations. Results were then reviewed for clinical accuracy by certified graders.

Using only undilated images (patients' pupils were not dilated), the EyeArt system's sensitivity was 95.5 per cent, and specificity was 86 per cent.

Only a small fraction of eyes required dilation to achieve an image good enough to be graded. When including these additional patients in the analysis, the sensitivity remained the same, specificity improved to 86.5 per cent, and gradability improved to 97.4 per cent.

More than 90 per cent of the eyes identified as positive by the EyeArt system had diabetic retinopathy or another eye disease per the reference standard.

"Accurate, real-time diagnosis holds great promise for the millions of patients living with diabetes. In addition to increased accessibility, a prompt diagnosis made possible with AI means identifying those at risk of blindness and getting them in front of an ophthalmologist for treatment before it is too late," said a Dr.

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Researchers develop robotic thread that may slip through brain's blood vessels

Researchers have developed a magnetically steerable, thread-like robot that may actively glide through narrow, winding pathways like the brain's tiny blood vessels. The study, revealed that the magnetically controlled device could one day deliver clot-reducing therapies in response to strokes or other brain blockages.

If acute stroke can be treated within the 1st 90 minutes or so, patients' survival rates could increase significantly, the researcher said.

If we could design a device to reverse blood vessel blockage within this ' golden hour', we could potentially avoid permanent brain damage. That's our hope. To clear blood clots in the brain, surgeons currently need to insert a thin wire through a patient's main artery, usually in the leg or groin, and manually rotate the wire up into the damaged brain vessel, guided  by a fluroscope that images the blood vessels using x-rays.

However, the procedure is physically taxing, requiring surgeons who must be specifically trained in the task, to endure repeated radiation exposure.

The researchers created a robotic thread core made from bendy, springy nickel-titanium alloy, and they coated the wire core in a rubbery paste filled with magnetic particles.

They then bonded the magnetic covering with a kind of hydrogel that gives the thread a slippery, friction-free surface, but does not affect the responsiveness or the magnetic particles, according to the study.

The researchers tested the thread in a life-size silicone replica of the brain's major blood vessels modeled after scanning an actual patient's brain. Those silicone vessels also have clots and abnormal sacs.

They filled the vessels with a liquid simulating the viscosity of blood, then successfully manipulated a large magnet around the model to steer the robot through the vessels' winding, narrow paths.

The team demonstrated that the thread's wire core can also be replaced with an optical fibre that can activate the laser once the robot reached a target region to clear blockages.

They are preparing to test the robotic thread in vivo, according to the researchers.

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