Associations of Edge-Detected and Manual-Traced Common Carotid Intima-Media Thickness Measurements With Framingham Risk Factors

Author:

Polak Joseph F.1,Pencina Michael J.1,Herrington David1,O'Leary Daniel H.1

Affiliation:

1. From the Department of Radiology (J.F.P.), Tufts Medical Center, Tufts University School of Medicine, Boston, MA; Department of Biostatistics (M.J.P.), Boston University School of Public Health, Framingham Heart Study, Boston, MA; Department of Internal Medicine/Cardiology (D.H.), Wake Forest University School of Medicine, Winston Salem, NC; Tufts University School of Medicine (D.H.O.), Boston, MA.

Abstract

Background and Purpose— Carotid intima-media thickness (IMT) is a marker of cardiovascular disease derived from ultrasound images of the carotid artery. In most outcome studies, human readers identify and trace the key IMT interfaces. We evaluate an alternate approach using automated edge detection. Methods— We studied a subset of 5640 participants with an average age 61.7 years (48% men) of the Multi-Ethnic Study of Atherosclerosis composed of whites, Chinese, Hispanic, and blacks that are part of the Multi-Ethnic Study of Atherosclerosis IMT progression study. Manual tracing IMT (mt-IMT) and edge-detected IMT (ed-IMT) measurements of the far wall of the common carotid artery served as outcome variables for multivariable linear regression models using Framingham cardiovascular risk factors and ethnicity as independent predictors. Results— Measurements of mt-IMT were obtainable in 99.9% (5633/5640) and measurements of ed-IMT were obtainable in 98.9% (5579/5640) of individuals. Average ed-IMT was 0.19 mm larger than mt-IMT. Inter-reader systematic differences (bias) in IMT measurements were apparent for mt-IMT but not ed-IMT. Based on complete data for 5538 individuals, associations of IMT with risk factors were stronger ( P <0.0001) for mt-IMT (model r 2 , 19.5%) than for ed-IMT (model r 2 , 18.5%). Conclusions— We conclude that this edge-detection process generates IMT values equivalent to manually traced ones because it preserves key associations with cardiovascular risk factors. It also decreases inter-reader bias, potentially making it applicable for use in cardiovascular risk assessment.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialised Nursing,Cardiology and Cardiovascular Medicine,Clinical Neurology

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