The study find that the Lung cancer screening using low-dose computed tomography (LDCT) ; is now recommend for certain populations; and while it has been shows to reduce mortality; there are persistent challenges with this technology; including inter-grader variability and high rates of false-positive and false-negative results.
Artificial intelligence (AI) ; may be able to help circumvent some of those limitations; suggests a new study .Researchers from Google trained a deep-learning algorithm to detect malignant lesions in the lungs from more than 42,000 CT scans. The algorithms then identify 11% fewer false positives and 5% fewer false negatives than train radiologists who reviewed the same scans.
While the results are provocative; the authors caution that these findings need to be clinically validated in large patient populations. The study is publish online May 20 in Nature Medicine. “In the study; we showed that the AI tool shows promise in better diagnosing patients with cancer, and better determining those who do not have cancer;” said study coauthor Mozziyar Etemadi, MD, PhD, a research assistant professor of anesthesiology at Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Accurate diagnosis of cancer
“All of the data used in the study were retrospective and the next step is to perform a prospective study to see if the tool, when used by a radiologist; can lead to earlier and more accurate diagnosis of cancer, and hopefully; better outcomes for patients.” Etemadi told Medscape Medical News that the research team is currently in the planning phase, but moving quickly toward going forward with it.
“In the ideal case, such a study would capture a large, diverse patient population, but this is a significant challenge;” said Etemadi. “Hospital computer systems are not designed to play nice with each other; let alone something as cutting edge as an AI algorithm that runs in the cloud. A big part of what my team is working on now is building this ‘middleware’ to make this a reality.”
The planning phase
He pointed out that work remains to be done, in collaboration with Google, to learn precisely how a radiologist or other physician would like to use the AI. Screening for lung cancer using low-dose computed tomography (LDCT) is recommended by the US Preventive Services Task Force for certain groups at high risk for the disease.
But a persistent problem with LDCT screening is the high rate of false positives. About a quarter (24%) of LDCT screening exams produce a positive result that requires follow-up; but 96% of these findings are false positives. This has prompted researchers to investigate new methods of differentiating malignant from benign nodules.