How AI is detecting lung cancer sooner
A new artificial intelligence tool called Sybil is helping doctors predict lung cancer risk years before it appears on scans, potentially closing gaps in current screening guidelines.
Standard lung cancer screening is conducted through low-dose CT scans, but only about 20% of eligible individuals undergo screening. Until 2022, guidelines recommended CT scans only for people aged 50 to 80 who smoked heavily and either still smoke or quit within the last 15 years.
"In fact, 50% of people diagnosed with lung cancer in the US every year would not have met the criteria for screening," said Dr. Lecia Sequist, a medical oncologist at Mass General Brigham Cancer Institute.
To address this gap, doctors at Mass General Brigham Cancer Institute collaborated with engineers at MIT to develop Sybil, an AI tool that analyzes a single CT scan and generates a risk score predicting the likelihood of developing lung cancer over a period of up to six years.
In 2023, researchers reported that Sybil achieved an accuracy rate of 86% to 94% in distinguishing high-risk patients from low-risk patients within a year.
"What Sybil is doing is something that the radiologists can't do, which is try and predict what's going to happen 1 year from now, 2 years from now, that may not be on the image today," Sequist said.
Sybil uses pattern recognition, trained on tens of thousands of scans, to detect biological signals invisible to the human eye.
"If someone has a CAT scan today and Sybil gives it a high risk score, what does that mean for the person? Should we be, you know, treating them in a different way now to mitigate their risk, to lower the chances of this happening to them in the future? We don't know if it will work in that way, but that's what we're hoping," Sequist said.
