A self-pay, artificial intelligence (AI)-enhanced breast cancer screening program could help improve breast cancer detection rates, according to new findings presented by Sorensen et al at the Radiological Society of North America (RSNA) 2024 Annual Meeting (Abstract R5B-SPBR-4).
Background
Despite showing potential in mammography as a “second set of eyes” for radiologists providing decision support, risk prediction, and other benefits, AI is not yet reimbursed by insurance—which could be slowing its adoption in clinical settings. Some practices have elected to offer enhanced workflows enabled by AI at additional cost, similar to the initial deployment of digital breast tomosynthesis.
Study Methods and Results
In the new study, researchers investigated the impact of a self-pay, AI-powered screening mammography program across 10 clinical practices, ranging from a few sites up to 64 sites at the largest practice. Women who enrolled in the program had U.S. Food and Drug Administration–compliant AI software applied to their mammograms. An expert breast radiologist provided a third safeguard review in cases where there was discordance between the first reviewer and the AI.
The researchers found that over one-third of the women chose to enroll in the self-pay, AI-enhanced program. Among the 747,604 women who received screening mammograms over an initial 12-month period, the overall cancer detection rate was on average 43% higher among those who enrolled compared with those who were unenrolled. The pattern of a substantially higher cancer detection rate in enrolled women was observed at all 10 practices.
Further analysis attributed 21% of the increase in cancer detection to the AI program. The researchers credited the remaining 22% increase in detection to the fact that higher-risk patients chose to enroll more frequently.
The researchers detailed that the recall rate was 21% higher among the enrolled vs unenrolled women. Notably, the positive predictive value for cancer was 15% higher among the enrolled women, indicating that each recall resulted in more cancer diagnoses in the enrolled population.
Conclusions
“These data indicate that many women are eager to utilize AI to enhance their screening mammogram, and when AI is coupled with a safeguard review, more cancers are found,” said senior study author Gregory Sorensen, MD, of DeepHealth in Massachusetts.
The researchers plan to better quantify the benefit of the AI-driven safeguard review with prospective randomized controlled trials that would eliminate the self-selection bias and provide the highest level of evidence.
“This is the first report on results from a program that provides an AI-powered enhanced review that patients can elect to enroll in,” noted lead study author Bryan Haslam, PhD, of DeepHealth. “The AI-driven enhanced review program leverages AI in a novel workflow to ensure women with suspicious findings get expert level care that could help detect many more breast cancers early. The number of women electing for this program is now at 36% and growing, and the rate of cancer detection continues to be substantially higher for those women,” he concluded.
Disclosure: For full disclosures of the study authors, visit reg.meeting.rsna.org.
