Use of B-mode ultrasound to examine preclinical markers of atherosclerosis: image quality may bias associations between adiposity and measures of vascular structure and function.
Magnussen CG., Thomson R., Juonala M., Viikari JSA., Dwyer T., Raitakari OT., Venn A.
OBJECTIVE: The purpose of this study was to examine the association between adiposity measures, ultrasound image quality, and preclinical markers of atherosclerosis in young adults. METHODS: B-mode ultrasound was used to obtain common carotid intima-media thickness and common carotid artery distensibility of 2265 and 1313 adults aged 24 to 39 years in two population-based studies: the Cardiovascular Risk in Young Finns and Childhood Determinants of Adult Health studies. Qualitative assessments of ultrasound image quality were obtained from each study (scored as 1, excellent; 2, average; and 3, poor) based on the ability to detect arterial interfaces and the amount of noise present in the image. RESULTS: Increased adiposity was associated with significantly increased odds (all P < .05) of average or poor carotid ultrasound image quality. Reduced image quality was associated with lower intima-media thickness in Young Finns (regression coefficient = -0.029; P = .01) and higher intima-media thickness in Childhood Determinants of Adult Health (regression coefficient = 0.013; P = .03) and lower distensibility levels in both studies (Young Finns, β = -.494; P < .01; Childhood Determinants of Adult Health: β = -.195; P < .01). We observed no differences (bias) in the association between adiposity measures and carotid intima-media thickness by image quality, but there was some evidence suggesting that the association between adiposity measures and carotid distensibility differed by image quality. CONCLUSIONS: Adiposity affects ultrasound image quality and has the potential to bias associations between adiposity and preclinical markers of atherosclerosis. Studies examining adiposity and ultrasound-derived measures of atherosclerosis should consider taking steps during the design and analysis phase to adequately account for variations in image quality to avoid any potential bias.