Endometriosis specialist Dr. Xiaoming Guan is working with a team of researchers to expedite the diagnosis of this painful disease through artificial intelligence (AI), preventing years of suffering as women search for relief.
“Currently, the use of MRI for diagnosing endometriosis can pose challenges, particularly in smaller centers where expertise may be limited,” said Dr. Guan, professor of obstetrics and gynecology at Baylor, fellowship director and chief of the division of Minimally Invasive Gynecologic Surgery.
“Using artificial intelligence based on an analysis of MRI imaging from confirmed cases, we’re developing an initial screening system that would scan a patient’s MRI and then indicate the likelihood they have endometriosis. In the future the system could also hopefully stage the disease and predict things like bowel endometriosis, endometrioma, and pelvic adhesions to help us determine other specialties needed during surgery.” Today, endometriosis can only be confirmed through laparoscopic surgery and biopsy.
As co-investigator, Dr. Guan is identifying the patients and MRI imaging needed to create the algorithm for the AI-based system, pulling from hundreds of cases he’s treated over the years.
A recognized leader in endometriosis excision surgery, Dr. Guan was recently elected to the board of the American Association of Gynecologic Laparoscopists (AAGL). “It’s a big deal to me,” he admitted, “and an honor to serve the largest organization supporting my field. With thousands of members from 110 countries, it’s also an opportunity to make a global impact on endometriosis through basic scientific research, training, and increased awareness of innovative approaches.”
He is one of the few surgeons in the world performing novel procedures like robotic transvaginal NOTES surgery for endometriosis resection. “We’ve performed close to 200 surgeries now, transvaginally removing all of the endometriosis,” said Dr. Guan. “Research shows this approach leads to less pain, faster recovery, and fewer pelvic adhesions compared to a transabdominal approach.”
The surgery can be technically challenging, he noted, requiring expertise in both endometriosis surgery and Natural Orifice Transluminal Endoscopic Surgery (NOTES). “I hope to provide training to help others use this approach so more patients around the world can benefit.”
“Anything that can benefit endometriosis patients, I'm willing to help,” said Dr. Guan.
In another published study, Dr. Guan used a new ICG (indocyanine green) robotic Firefly technique to reduce complications and surgical time in a complex stage 4 endometriosis case. The study found that using this fluorescent green dye enabled the team to quickly identify endometriosis tissue and reduced the risk of urethral and bowel injury during a robotic-assisted transvaginal NOTES hysterectomy with endometriosis resection.