By: Sara Hoover

Dr. Khan Iftekharuddin may not be restoring vision to the blind yet, but the associate professor of electrical and computer engineering in the Herff College of Engineering and his collaborator, Dr. Pinakin Gunvant, are doing the next best thing. They’re catching glaucoma more accurately in patients than ever before thanks to an old technique applied in a new way.

For the past seven years, Gunvant, assistant professor at the Southern College of Optometry, has focused on improving diagnostic techniques used in detecting glaucoma.

Early detection is a key to treating glaucoma, according to Iftekharuddin.

“There was a need to look at the entire region of the back of the eye rather than only an isolated region around the back of the eye as done by most analyses. That required a different approach,” Gunvant said.

He began researching engineering schools in the Memphis area to find a collaborator and came across Iftekharuddin’s Web page and realized his fractal techniques might be the perfect fit. The collaboration began in Fall 2008.

“Why don’t we apply fractal analysis and see if it works?” said Gunvant. “We just got lucky that we got a quick breakthrough automatically rather than requiring the technique to be adjusted for multiple things.”

Fractal analysis identifies a pattern in a particular image or signal. It has been shown to have a higher accuracy rate of identifying glaucoma indicators than standard testing methods.

Iftekharuddin serves as the “engineering brain” behind the research. Gunvant brings the medical training and an acute understanding of glaucoma, a disease in which the optical nerve becomes damaged, leading to progressive and irreversible loss of vision.

In Gunvant’s glaucoma testing, light is beamed through the back of the retina to measure the thickness of retinal tissue at certain points, which can indicate glaucoma. He collects the data sets from patients and sends the images to Iftekharuddin’s lab for fractal analysis.

“Our job is to analyze these images, write the computer and mathematical algorithms to analyze and interpret the results and summarize it,” said Iftekharuddin, whose other fractal analysis work includes finding infrared targets for the Army, face recognition development for the National Science Foundation and brain tumor research with St. Jude Children’s Research Hospital.

“It’s higher than standardized machine classifiers,” said Gunvant of Iftekharuddin’s fractal analysis. “We can’t claim that this necessarily beats out all the other techniques available. However, when compared to the standard machine classifier, fractal analysis quite significantly beats the classifier in the range of 13 percent.”

Adds Iftekharuddin, “Commonly available medical devices, such as scanning laser polarimeters, already come with built-in algorithms. Those algorithms give accuracy around 85 percent. Using our fractal technique, we are able to bring it up to around 97 to 98 percent. The accuracy has improved using our technique.”

The medical application of fractal analysis is novel.

Dr. Khan Iftekharuddin, associate professor of electrical and computer engineering in the Herff College of Engineering, is researching ways to enhance testing of glaucoma in an effort to better manage the disease.

“This is breakthrough. Fractal analysis has never been utilized for glaucoma management,” said Gunvant. “The technique was established before. However, in glaucoma — to the best of our knowledge — this has been the first attempt of the application of this technique.”

Iftekharuddin adds, “The goals are to see if we can do anything better than what’s already out there. If we’re successful, we should be able to predict glaucoma earlier on. Like any other disease, if you detect it earlier, the chances are the prognosis is better, treatment is better.”

Gunvant says the disease affects about 3 percent of the world’s population.

“Glaucoma has been described as a silent thief of vision,” he said. “By the time a person is identified with having the disease, they’ve already lost about 30 to 50 percent of their retinal cells. This is irreversible vision loss. So any early identification technique will be a great asset. Our research is going to be quite beneficial.”

The team would like to not only identify who does and does not have glaucoma, but the disease’s progression.

“You want to find those individuals who have the disease first,” said Gunvant. “And as a subsequent bigger goal, we want to identify the individuals who are having progressive damage. Because this is such a slow, progressive disease, it takes about seven to 10 years before you can identify the progression. Any technique that can identify patients who are undergoing progression of the disease is very useful.

“We could then act upon trying to save the vision of those individuals. That’s the next phase to the application of this procedure.”

The next step for the research also includes moving beyond two-dimensional data into three-dimensional.

“In some respects, we are yet to make our biggest breakthrough in this new technique,” said Gunvant. “The most important aspect of this analysis would be to apply this to three-dimensional data of the back of the eye. For the next two years, we are going to apply a similar technique to the retinal nerve fiber layer at the back of the eye in trying to better predict glaucoma.”

The pair applied for a patent in September, along with a third investigator, U of M doctoral student Paul Kim.

“This is really when (students) learn the tricks of the trade, how to do research and also how to guide other people,” said Iftekharuddin. “I’m mentoring him at the technical part, whereas my colleague is looking at the clinical part, so (Kim) gets balanced training.”

With a patent pending, the team has presented at conferences and has applied for funding. Gunvant received a grant from the Assisi Foundation of Memphis, which partially covers Kim’s tuition and stipend for the next two years. They hope to eventually apply for grants from the NIH’s National Eye Institute.

Since the technique works for identifying glaucoma so well, there is a good chance it may also work for other degenerative retinal diseases.

View a video of the research here.