Research hub to discover new ways to diagnose and treat endometriosis

Allison Vorp, who was diagnosed with endometriosis in 2021, experienced severe pains, but before getting diagnosed didn’t fully understand what was wrong. 

A team of researchers have come together to create the Hub for Endometriosis Research in Pittsburgh to discover new ways to diagnose endometriosis and find more information on the disease.

HER includes a dozen researchers and clinicians across several Pitt schools, including the Swanson School of Engineering and School of Medicine, as well as from UPMC Magee-Womens Hospital and the Magee-Womens Research Institute.

“When I was in my early 40s, I got a really bad pain in my lower right side, and it was so bad I ended up going to the emergency room,” Allison Vorp said. “They believed it was an ovarian cyst and it should go away and I was supposed to go home.”

Allison Vorp said the original pain went away, but she would periodically get pains in the same area. The pains became much worse and the time between them became shorter.

Allison Vorp went to physical therapy because her doctors believed she had arthritis. She had CT scans and ultrasounds in order to get a diagnosis. 

“I had been reading a lot about it, too, and I came across endometriosis, and I had vaguely heard of it but didn’t know what it was,” Allison Vorp said. “I mentioned it to my gynecologist, and my gynecologist said, ‘I am going to refer you to the pelvic pain clinic.’”

Allison Vorp was evaluated by the surgeon at the pelvic pain clinic. She recalled that within moments of speaking to the surgeon she had gotten diagnosed with endometriosis.

“When they did my surgery, they excised suspicious tissue and sent it to pathology, since it is the only real way to say for sure that it is endo. I had it everywhere. I had it on my Fallopian tubes and on my digestive tract and on my ovaries,” Allison Vorp said.

After Allison Vorp was diagnosed with endometriosis, her husband David Vorp, senior associate dean for research and facilities at the Swanson School of Engineering, a bioengineering professor and director of Pitt’s Vascular Bioengineering Lab, wanted to understand the disease.

“I wanted to learn more about the disease and how I can support my wife and what to expect in her journey,” David Vorp said. “As she was suffering and hopefully getting treated for it, I was taken aback by how little is known about endometriosis and how little research is currently being done into such a prevalent disease.”

David Vorp then reached out to Isabelle Chickanosky, an incoming doctoral student on his research team who had previously expressed interest in studying endometriosis, to see if she would be interested in researching it with him.

“I went back to Isabelle and said, ‘Remember all those months ago how much you were interested in studying endometriosis? Well, I now have an interest in it, and I want you to teach me all that you know about it. Let’s see if it is something we might be able to work on,’” David Vorp said.

David Vorp and Chickanosky sat down for an hour each week to brainstorm the ways that bioengineering approaches could contribute to the diagnoses or treatment of endometriosis.

Together they came up with the idea of using machine learning, a type of AI, to try and diagnose endometriosis along with looking at the ways cells interact in the body to understand why they attach to certain spots, which leads to the disease manifesting as pain.

“Right now, the only way to diagnose is through surgery, and the surgeons go in and either find the endometriosis or they don’t. Unfortunately, about 50% of these surgeries that are done on women that have symptoms similar to endometriosis are negative. The woman doesn’t have endometriosis and doesn’t get an answer for her painful symptoms,” David Vorp said.

Through his research, David Vorp found that endometriosis is more prevalent than commonly thought. 

“At any given time, 10% of women that are of childbearing age — that’s over 6.5 million in the United States and 200 million worldwide — have endometriosis and many of them don’t even know,” David Vorp said.

David Vorp said a lot of the same symptoms for endometriosis can come from different things, which is why it is so difficult to diagnose this disease.

“We are hoping that this machine learning approach will at least give a better sense of whether it is endometriosis that is afflicting a particular woman and give a little more confidence before surgery is performed.” David Vorp said.

David Vorp said one of the main issues that HER faces is funding.

“It’s an underfunded disease,” David Vorp said. “I always like to say if it was a disease of the white male, it would have a lot of funding put into it.”

David Vorp said without much funding it is hard to make much progress, which has been a big challenge.

Nicole Donnellan, a gynecologic surgeon who helped found HER, said she agrees that funding has proven a major issue for them.

“A lot of times funding, especially governmental, you have to prove that you can work together, so you are like, we have this great concept but none of us have worked together,” Donnellan said.

Donnellan mentioned that this struggle for funding isn’t specific to HER, but is the reality of endometriosis research in general.

“You have to get funds off the ground and prove that it’s something worth putting money into,” Donnellan said.

Despite the struggle for funding, those collaborating at HER continue their research in hopes of helping women who struggle with endometriosis.

“The goals of HER are not only to advance research, [but also] to advance advocacy and education and to overall help enhance the care of individuals that have endometriosis,” Donnellan said. “I think the impact is not only regional, the patients of Western Pennsylvania, but through academia and serving as a role model for other institutions.”