Diagnostic screening programs help catch cancer, abnormalities or other diseases before they reach an advanced stage, saving lives and healthcare costs. Screening programs include, lung, breast, prostate, and cervical cancer, among many others.
There are no standards requiring radiologists to report on the presence of BACs, even though up to half of referring providers have indicated they would prefer to be made aware of the finding.
Breast artery calcifications are already visible when radiologists review mammograms, but nothing typically happens with them. Researchers aimed to see if AI could help translate those findings into an easy-to-understand cardiovascular risk score.
Despite the great progress that has been made toward the clinical implementation of AI, new data caution against trusting the technology as a single reader in certain settings.
Although current guidelines recommend radiologists evaluate CAC on all non-gated, non-contrast chest CT scans, the authors of the study note that these guidelines are not consistently followed.
The results of a survey completed by more than 13,000 respondents who were eligible for the cancer screening revealed that less than 2% of eligible participants underwent CTC exams.
Researchers reported that the artificial intelligence system was able to interpret more than 114,000 screening mammograms using a reading protocol with high sensitivity and specificity.
These findings underscore the need for better implementation of shared decision-making (SDM) models, as well as more thorough counseling documentation, as low-dose CT (LDCT) lung screen coverage is dependent on these factors, experts suggested.
The downward trend in annual mammography adherence should serve as a call to action for new processes to engage breast cancer survivors, physicians urged.