Washington D.C. [USA], April 27 (ANI): In a recent study, researchers have developed an algorithm within AI-Rad Companion, which examines chest scans, provides results comparable with lung function tests, which measure how forcefully a person can exhale.
The study shows that artificial intelligence (AI) software works are the first step towards possibly using chest scans to quantify the severity of the lung disease and track the progress of treatment.
"Everybody has a different trigger threshold for what they would call normal and what they would call disease," said U Joseph Schoepf, MD, director of cardiovascular imaging for MUSC Health and assistant dean for clinical research at the Medical University of South Carolina College of Medicine.
"In the past, if you lost lung tissue, that was it. The lung tissue was gone, and there was very little you could do in terms of therapy to help patients," he said.
Schoepf was a principal investigator in a study looking at the results of Siemens Healthineers' AI-Rad Companion as compared with traditional lung function tests. The study has been published online in the American Journal of Roentgenology.
But with advancements in treatment in recent years has come an increased interest in objectively classifying the disease, Schoepf said. That's where artificial intelligence and imaging could come into play.
In the study, researchers went back and looked at the chest scans and lung function tests of 141 people. Chest scans aren't currently part of the guidelines for diagnosing chronic obstructive pulmonary disease, an umbrella term that includes emphysema, chronic bronchitis and other lung diseases, Schoepf said, because there haven't been an objective means to evaluate scans.
However, he anticipates a role for imaging scans if it can be shown that they offer a benefit in terms of objectivity and quantification.
Philipp Hoelzer, a customer engagement manager with Siemens Healthineers, said having an objective measurement could help in assessing the value of new treatments or drugs. The Siemens Healthineers team sees the program as a way for artificial intelligence to work in tandem with the clinical expertise of radiologists, he said.
"Taking away manual, repetitive tasks, like those that require a lot of measurement, is of great benefit to a radiologist, especially when reading cases that may have 20 or more nodules," he said. "Interpreting the images, and the abstract thinking that goes along with it will remain with the radiologist."
The program can also offer concrete aid to doctors trying to impress upon patients the necessity of making changes. It can create a 3D model of the patient's lungs, showing the existing damage.
"If you could visualise it and provide the information in image terms, you could better communicate with the patient and hopefully nudge the patient into smoking cessation or lifestyle changes," Hoelzer said.
A potential additional benefit is that AI-Rad Companion automatically looks for problems across multiple organ systems, including measuring the aorta and bone density.
As Schoepf moves into a prospective study phase, he'll be examining whether artificial intelligence finds things that humans miss. And it can be easy for humans to miss problems that they aren't specifically looking for, he said.
"We're told the patient has these types of symptoms, and then we basically go look for stuff that could explain those symptoms. So, we're often blind to things that do not necessarily relate to the organ system we're interested in," he said.
It can also be difficult for humans to create an accurate measurement of a three-dimensional structure within the body from a two-dimensional scan - something that isn't a problem for the artificial intelligence program. It can automatically combine multiple 2D images to produce 3D measurements.
Schoepf wants to see whether the program improves patient management by prompting early treatment of problems, like a widened aorta or decreased bone density, before the problems become painfully obvious to both doctor and patient. (ANI)