Incidental Evolution

Last week brought a wave of studies that either highlighted how findings in common imaging exams could add value in completely different clinical areas, or showed how incidentals could find a home in established clinical workflows. That might not be welcomed news among the many radiologists who view incidentals as a clinical slippery slope, but it’s another sign that the incidental evolution is gaining momentum.

Left Atrial Dementia Marker – A new JAMA study showed that echocardiographic left atrial function measurements can be used to identify individuals with higher dementia risks, in addition to supporting cardiovascular diagnosis. Analysis of 4,096 participants’ echo exams and 6-year outcomes (75yr avg. age; 531 developed dementia) revealed that lower left atrial function (e.g. reservoir strain, conduit strain, contractile strain, active emptying fraction, emptying fraction) has a statistically significant association with developing dementia (1.43 to 1.98 hazard ratios).

BACs and CVD – A Kaiser Permanente study added more evidence supporting breast arterial calcifications’ value as a cardiovascular disease risk factor. The researchers analyzed 5,059 women’s digital mammography exams (26.5% w/ BACs), finding that women with BACs had a 51% higher risk of developing atherosclerotic CVD and a 23% higher risk of developing any type of CVD over 6.5-years. This is far from the first study to tie BACs to CVD risk, but it came with a high level of credibility (large/observational study, published on Circulation) and generated quite a bit of media attention.

Auto CAC Pathway – A Journal of Digital Imaging study highlighted how coronary artery calcium scores (CAC scores) could be integrated into standard cardiovascular disease (CVD) risk systems, potentially streamlining CAC AI adoption. The researchers used an FDA-cleared AI model (believed to be from Nanox AI) to screen 14,135 patients’ existing CTs (470 who experienced CVD within 5yrs) and then combined their CAC scores with the ACC/AHA’s PCE risk system. The AI-augmented PCE predictions outperformed standard PCE predictions (sensitivity: 57% vs. 53%; specificity: 70% vs. 67%), without requiring additional scans or diagnostic workflows.

Northwestern Follows-Up – A new NEJM study highlighted the impressive results of Northwestern Medicine’s lung nodule follow-up system, which uses NLP to identify suspicious nodules and then initiates a follow-up workflow (prompts physicians, notifies patients, tracks follow-ups). Over 13 months, the system screened over 570k imaging studies, flagging 29k exams for follow-up (77.1% sensitivity, 99.5% specificity, 90.3% PPV), and tracked over 2,400 follow-ups to completion.

The Takeaway
Last week’s batch of studies serve as yet another reminder that common imaging exams could serve broader clinical roles the future, either by creating new risk-based incidental pathways (LA function for dementia; BAC for CVD), catching more undetected incidentals (AI CAC scoring), or by formalizing how incidentals are brought into clinical pathways (e.g. adding CAC to PCEs; leveraging NLP for follow-ups).

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-- The Imaging Wire team