The novel tool could result in earlier prostate cancer diagnoses and less invasive testing, although a prostate cancer expert cautioned that the model makes multiple assumptions and has not been validated.
A mathematical model might someday noninvasively and accurately predict a prostate cancer tumor’s evolution, velocity of growth, and more.
In the years to come, the model studied could result in earlier prostate cancer diagnoses and less invasive testing, although a prostate cancer expert cautioned that the model makes multiple assumptions and has not been validated.
An international group of researchers, reporting their findings online in Proceedings of the National Academy of Sciences of the United States of America (Nov. 16, 2016), used medical images to do a tissue-scale, personalized computer simulation of prostate cancer growth in an actual patient. Researchers say the data generated are easy for urologists to interpret, showing an individual’s predicted prostatic tumor growth, the cancer’s growth pattern, and velocity of growth.
“There is a lot of room for improvement in both the diagnosis and management of prostate cancer. We’re using computer modeling to capture the behavior of prostate tumor growth which will hopefully lead to minimally invasive predictive procedures which can be used in clinical practice,” said study coauthor Michael Scott, PhD, of Brigham Young University, Provo, UT in a press release from that institution.
Study co-author Thomas J. R. Hughes, PhD, of the Institute for Computational Engineering and Sciences at the University of Texas, Austin, told Urology Times that the model represents a new dimension in medicine, called predictive medicine.
“It’s part of a theme that is developing in medicine, in which methodologies that emanate from science and engineering are being integrated into medical processes,” Dr. Hughes said. “There is already a company that is pioneering such patient diagnostic modeling in coronary artery disease, and it’s making quite a splash.”
The FDA-approved HeartFlow technology uses standard computed tomography scan data to noninvasively develop a 3-dimensional model of the coronary arteries, analyzing the impact that blockages have on blood flow. The HeartFlow analysis accomplishes essentially the same as invasive angiographies done to determine functional significance of a blockage in an artery, according to Dr. Hughes, who is a stockholder in the company and a scientific adviser.
“In prostate cancer, we’re trying to do something similar. We’re trying to create mathematical models that eventually would take all the information-the genomic information, anatomical information, physiological information, etc.-and plug it into a model,” he said.
Next: How the model works
Starting with an image, the model would generate information about how the patient’s prostate tumor would evolve, at what time rate, and how aggressively. It will look at the tumor’s geometric significance and whether the tumor will penetrate the capsule in a short or long amount of time.
“We demonstrated it on the anatomy of a real patient with a current version of the model. I consider it an initiatory version. The model will become more complex with time. But I think the principle is illustrative. You would predict the growth of the tumor. You would be able to see what it would look like and, perhaps more importantly, you could get the velocity of growth. Will it take a few months to grow like that or 30 years? That is a big difference and very important information,” Dr. Hughes said.
Prostate cancer diagnosis is in a sorry state, according to Dr. Hughes.
“It is misdiagnosed regularly and it leaves most men in a situation where you’d rather be safe than sorry and go for a radical prostatectomy, radiation, or other impactful intervention. Urologists need much better diagnostic tools. So this brings computing and modern technology to the party, so to speak, and eventually the possibility of being able to do this on an individual patient basis-not on a statistical basis,” he said.
Urology Times Editorial Council member Stacy Loeb, MD, MSc, who was not an author on the paper, says this model designed to simulate prostate cancer growth makes multiple assumptions and has not yet been validated.
“A lot more investigation is needed before this type of model could be used to guide clinical decisions,” said Dr. Loeb, of New York University Langone Medical Center, New York. “The authors should be congratulated on a significant amount of work to apply mathematical oncology to prostate cancer. There are still many unanswered questions in prostate cancer diagnosis and management, so that is an important area of investigation, and it is interesting to draw from other disciplines for new methods that might be useful to help answer these questions in the future.”
Research for image-based, computational modeling in prostate cancer is in the early phases and it is very difficult to estimate how long it will take to reach the clinic, Dr. Hughes said.
Dr. Hughes is co-holder of a patent for this technology.
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