"In my case, the biopsies came out cancerous," says Chessin, 60, who underwent robotic surgery for intermediate-grade prostate cancer at University Hospitals Cleveland Medical Center.
Although he needed a biopsy, as most patients today do, advances in radiologic technology may make such invasive measures unnecessary in the future. Researchers are developing better imaging techniques and algorithms—a form of computer science called artificial intelligence, in which machines learn and execute tasks that typically require human brain power.
This innovation may enhance diagnostic precision and promptness. But it also brings ethical concerns to the forefront of the conversation, highlighting the potential for invasion of privacy, unequal patient access, and less physician involvement in patient care.
A National Academy of Medicine Special Publication, released in December, emphasizes that setting industry-wide standards for use in patient care is essential to AI's responsible and transparent implementation as the industry grapples with voluminous quantities of data. The technology should be viewed as a tool to supplement decision-making by highly trained professionals, not to replace it.
MRI--a test that uses powerful magnets, radio waves, and a computer to take detailed images inside the body--has become highly accurate in detecting aggressive prostate cancer, but its reliability is more limited in identifying low and intermediate grades of malignancy. That's why Chessin opted to have his prostate removed rather than take the chance of missing anything more suspicious that could develop.
His urologist, Lee Ponsky, says AI's most significant impact is yet to come. He hopes University Hospitals Cleveland Medical Center's collaboration with research scientists at its academic affiliate, Case Western Reserve University, will lead to the invention of a virtual biopsy.
A National Cancer Institute five-year grant is funding the project, launched in 2017, to develop a combined MRI and computerized tool to support more accurate detection and grading of prostate cancer. Such a tool would be "the closest to a crystal ball that we can get," says Ponsky, professor and chairman of the Urology Institute.
In situations where AI has guided diagnostics, radiologists' interpretations of breast, lung, and prostate lesions have improved as much as 25 percent, says Anant Madabhushi, a biomedical engineer and director of the Center for Computational Imaging and Personalized Diagnostics at Case Western Reserve, who is collaborating with Ponsky. "AI is very nascent," Madabhushi says, estimating that fewer than 10 percent of niche academic medical centers have used it. "We are still optimizing and validating the AI and virtual biopsy technology."
In October, several North American and European professional organizations of radiologists, imaging informaticists, and medical physicists released a joint statement on the ethics of AI. "Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future," reads the statement, published in the Journal of the American College of Radiology. "The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes."
The statement's leader author, radiologist J. Raymond Geis, says "there's no question" that machines equipped with artificial intelligence "can extract more information than two human eyes" by spotting very subtle patterns in pixels. Yet, such nuances are "only part of the bigger picture of taking care of a patient," says Geis, a senior scientist with the American College of Radiology's Data Science Institute. "We have to be able to combine that with knowledge of what those pixels mean."
Setting ethical standards is high on all physicians' radar because the intricacies of each patient's medical record are factored into the computer's algorithm, which, in turn, may be used to help interpret other patients' scans, says radiologist Frank Rybicki, vice chair of operations and quality at the University of Cincinnati's department of radiology. Although obtaining patients' informed consent in writing is currently necessary, ethical dilemmas arise if and when patients have a change of heart about the use of their private health information. It is likely that removing individual data may be possible for some algorithms but not others, Rybicki says.
The information is de-identified to protect patient privacy. Using it to advance research is akin to analyzing human tissue removed in surgical procedures with the goal of discovering new medicines to fight disease, says Maryellen Giger, a University of Chicago medical physicist who studies computer-aided diagnosis in cancers of the breast, lung, and prostate, as well as bone diseases. Physicians who become adept at using AI to augment their interpretation of imaging will be ahead of the curve, she says.
As with other new discoveries, patient access and equality come into play. While AI appears to "have potential to improve over human performance in certain contexts," an algorithm's design may result in greater accuracy for certain groups of patients, says Lucia M. Rafanelli, a political theorist at The George Washington University. This "could have a disproportionately bad impact on one segment of the population."
Overreliance on new technology also poses concern when humans "outsource the process to a machine." Over time, they may cease developing and refining the skills they used before the invention became available, said Chloe Bakalar, a visiting research collaborator at Princeton University's Center for Information Technology Policy.
Shota Kuwahara, a DAWN employee with muscular dystrophy. Ory Labs, Inc. 