Researchers used advanced computer imaging technology to create a three-dimensional computer reconstruction of a patient’s bladder. The technique, which works on any hollow organ, could help doctors locate tumors or other disorders and prepare for surgery.
March 22, 2017 - By Jackie Flynn
The way doctors examine the bladder for tumors or stones is like exploring the contours of a cave with a flashlight. Using cameras attached to long, flexible instruments called endoscopes, they find that it’s sometimes difficult to orient the location of masses within the bladder’s blood-vessel-lined walls.
This could change with a new computer-vision technique developed by Stanford researchers that creates three-dimensional bladder reconstructions out of the endoscope’s otherwise fleeting images. With this fusion of medicine and engineering, doctors could develop organ maps, better prepare for operations and detect early cancer recurrences.
“The beauty of this project is that we can take data that doctors are already collecting,” said Audrey Bowden, PhD, assistant professor of electrical engineering. A paper describing the work was published online March 8 in Biomedical Optics Express. Bowden shares senior authorship with Joseph Liao, MD, an associate professor of urology. The lead author is Kristen Lurie, PhD, a former postdoctoral scholar at Stanford who is now a software engineer at Google
Bladder cancer has among the highest recurrence rates of any cancer. Fifty to 70 percent of tumors return after removal, according to Liao. Being able to see each patient’s bladder as a digital 3-D model could improve surgical planning and help doctors monitor cancer recurrence.
“Endoscopy of the bladder, called cystoscopy, is an integral part of cancer management. Anything you can do to improve endoscopy is helpful,” Liao said. “Surgeons are always looking for better ways to see cancer in order to remove it more effectively.”
Broadly applicable technique
One of the technique’s advantages is that doctors don’t have to buy new hardware or modify their techniques significantly. Through the use of advanced computer-vision algorithms, the team reconstructed the shape and internal appearance of a bladder using the video footage from a routine cystoscopy, which would ordinarily have been discarded or not recorded in the first place.
“In endoscopy, we generate a lot of data, but currently they’re just tossed away,” said Liao.
Although the team developed the technique for the bladder, it could be applied to other hollow organs where doctors routinely perform endoscopy, including the stomach or colon. “We were the first group to achieve complete 3-D bladder models using standard clinical equipment, which makes this research ripe for rapid translation to clinical practice,” Lurie said.
According to Liao, these three-dimensional images could help doctors prepare for surgery. Lesions, tumors and scars in the bladder are hard to find, both initially and during surgery.
“Sometimes you don’t have a sense — where was I in the bladder?” Liao said. Seeing a three-dimensional rendering of an organ before operating, like having a map before embarking on a trip, could make the procedure easier for doctors. Other potential applications include using the digital 3-D reconstruction as a visual medical record.
To test the accuracy of their bladder reconstruction, the team first created a model based on endoscopy images taken in a three-dimensional-printed bladder, known as a tissue phantom. Because the details of the tissue phantom are known, the researchers could directly compare it to their rendering. According to Bowden, tissue phantoms provide a standard for biological modeling analysis. The team found that its three-dimensional rendering matched the tissue phantom with few errors.
This technique is the first of its kind and still has room for improvement, the researchers said. Primarily, the 3-D models tend to flatten out bumps on the bladder wall, including tumors. With the model alone, this may make tumors harder to spot. The team is now working to advance the realism, in shape and detail, of the models.
Future directions, according to the researchers, include using the algorithm for disease and cancer monitoring within the bladder over time to detect subtle changes, as well as combining it with other imaging technologies.
“The technology has immense potential, not to mention the fun factor to be able to navigate around a virtual organ,” Liao said.
The other Stanford co-author of the paper is Dimitar Zlatev, MD, a resident in urology. A researcher at Max Planck Institute in Germany also contributed to the work.
This research was supported by the National Science Foundation and the Max Planck Center for Visual Computing and Communication.
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