Underreporting of Coronary Stents in LDCT for Lung Cancer Screening and Their Differentiation From Severe Coronary Artery Calcifications.

Abstract

Lung Cancer (LC) screening with low-dose CT (LDCT) is recommended in smokers and former smokers irrespective of cardiovascular disease (CVD) history. Differentiating coronary stents from moderate-to-severe coronary artery calcifications (CACs) on LDCT examinations can be challenging and have clinical implications. We hypothesized that coronary stents are inadequately reported in screening LDCT examinations and conducted a retrospective analysis nested within an LC screening study. Moreover, we devised a postprocessing procedure to differentiate coronary stents and severe CACs in LDCT examinations and assessed its potential. Among 592 participants with detailed CVD history at baseline, the LDCT report mentioned coronary stents in 13 and severe CACs in 60 of 73 (12.3%). Two radiologists independently and blindly reviewed the LDCT examinations, providing a binary judgment (yes/no) on stent presence using images optimized with a window setting optimized to view detail in bone (window width 1800 to 2000 HU and window level 300 to 500 HU) reformatted parallel or perpendicular to the coronary arteries. The review identified stents in 26 subjects and was inconclusive in 2. On images viewed with such "bone" window setting, stents appeared as "tram-track" (large stents) or "pencil-lead" (narrow stents) configurations in parallel views, and as a "rim-of-wheel" shape in perpendicular views. In contrast, CACs lacked these configurations due to their irregular distribution along vessel walls. No difference in attenuation was observed between stents and severe CACs. Concordance with the history of PTCA with stent placement was 42.8% (12/28) for the original LDCT reports and 92.8% (26/28) for the review ( P =0.0014). Our study suggests that coronary stents are often under-reported in screening LDCT, but their characteristic shapes on images viewed with a "bone" window setting with multiplanar reformatting can aid in accurate identification.