Associations of edge-detected and manual-traced common carotid artery intima-media thickness with incident peripheral artery disease: The Multi-Ethnic Study of Atherosclerosis

2019 ◽  
Vol 24 (4) ◽  
pp. 306-312
Author(s):  
Joseph F Polak ◽  
David Herrington ◽  
Daniel H O’Leary

Common carotid artery (CCA) intima-media thickness (IMT) is associated with coronary heart disease and can be measured on ultrasound images either by hand or with an automated edge detector. The association of CCA IMT with incident peripheral artery disease (PAD) is poorly studied. We studied 5467 participants of the Multi-Ethnic Study of Atherosclerosis composed of non-Hispanic white, Chinese, Hispanic, and African American participants with a mean age of 61.9 years (47.8% men). Framingham Risk Factors, manual-traced IMT (mt-IMT), and edge-detected IMT (ed-IMT) were entered into multivariable Cox proportional hazards models with incident PAD as the outcome. There were 87 events during a median follow-up of 12.2 years. In fully adjusted models and expressing the hazard ratios (HR) as an increment in SD values, both mt-IMT and ed-IMT were significantly associated with incident PAD: HR 1.36 (95% CI: 1.15, 1.61) and 1.29 (95% CI: 1.04, 1.60), respectively. We conclude that ed- and mt-CCA IMT measurements are associated with incident PAD. ClinicalTrials.gov Identifier: NCT00063440

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Qiang Li ◽  
Wei Zhang ◽  
Xin Guan ◽  
Yu Bai ◽  
Jing Jia

The intima-media thickness (IMT) of common carotid artery (CCA) can serve as an important indicator for the assessment of cardiovascular diseases (CVDs). In this paper an improved approach for automatic IMT measurement with low complexity and high accuracy is presented. 100 ultrasound images from 100 patients were tested with the proposed approach. The ground truth (GT) of the IMT was manually measured for six times and averaged, while the automatic segmented (AS) IMT was computed by the algorithm proposed in this paper. The mean difference ± standard deviation between AS and GT IMT is 0.0231 ± 0.0348 mm, and the correlation coefficient between them is 0.9629. The computational time is 0.3223 s per image with MATLAB under Windows XP on an Intel Core 2 Duo CPU E7500 @2.93 GHz. The proposed algorithm has the potential to achieve real-time measurement under Visual Studio.


Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Joseph F Polak ◽  
Moyses Szklo ◽  
Daniel H O'Leary

Background: Intima-media thickness (IMT) as measured on ultrasound images of the common carotid artery (CCA) is associated with cardiovascular events and used to measure the effects of lipid lowering interventions. Far wall CCA IMT is favored over near wall IMT based on the physics of ultrasound. Materials and Methods: We studied 6606 members of the Multi-Ethnic Study of Atherosclerosis (MESA), a longitudinal cohort study (mean age 62.1 years; 52.7% female) who had near wall and far wall CCA IMT measurements. Multivariable linear regression models were used to estimate model goodness-of-fit of near wall IMT, far wall IMT, and mean IMT with Framingham risk factors (FRF). Multivariable Cox proportional hazards models were used to estimate hazard ratios for incident coronary heart disease (CHD) events for each IMT variable. Change in Harrell’s C-statistic was used to compare the incremental value of each IMT variable when added to FRF. Results: Mean IMT had the strongest association with risk factors (R2 = 0.31), followed by the near wall (R2 = 0.26) and far wall IMT (R2 = 0.22). Far wall IMT improved the prediction of coronary artery disease events (change in C statistic: 0.009; 95% Confidence Intervals: 0.004, 0.015; p= 0.001) as did mean IMT (p=0.033) but near wall IMT did not. Conclusion: Far wall CCA IMT had the strongest association with incident CHD whereas combined near wall and far wall IMT had the strongest association with risk factors. Selected IMT variables may give different results in intervention trials than in outcome studies.


2019 ◽  
Vol 21 (10) ◽  
pp. 1152-1159 ◽  
Author(s):  
Parveen K Garg ◽  
Petra Buzkova ◽  
Zahra Meyghani ◽  
Matthew J Budoff ◽  
Joao Lima ◽  
...  

Abstract Aims The detection of cardiac valvular calcification on routine imaging may provide an opportunity to identify individuals at increased risk for peripheral artery disease (PAD). We investigated the associations of aortic valvular calcification (AVC) and mitral annular calcification (MAC) with risk of developing clinical PAD or a low ankle–brachial index (ABI). Methods and results AVC and MAC were measured on cardiac computed tomography in 6778 Multi-Ethnic Study of Atherosclerosis participants without baseline PAD between 2000 and 2002. Clinical PAD was ascertained through 2015. Incident low ABI, defined as ABI <0.9 and decline of ≥0.15, was assessed among 5762 individuals who had an ABI >0.9 at baseline and at least one follow-up ABI measurement 3–10 years later. Adjusted Cox proportional hazards and Poisson regression modelling were used to determine the association of valvular calcification with clinical PAD and low ABI, respectively. There were 117 clinical PAD and 198 low ABI events that occurred over a median follow-up of 14 years and 9.2 years, respectively. The presence of MAC was associated with an increased risk of clinical PAD [hazard ratio 1.79; 95% confidence interval (CI) 1.04–3.05] but not a low ABI (rate ratio 1.28; 95% CI 0.75–2.19). No significant associations were noted for the presence of AVC and risk of either clinical PAD. Conclusion MAC is associated with an increased risk of developing clinical PAD. Future studies are needed to corroborate our findings and better understand whether MAC holds any predictive value as a risk marker for PAD.


2013 ◽  
Vol 52 (2) ◽  
pp. 169-181 ◽  
Author(s):  
Rosa-María Menchón-Lara ◽  
María-Consuelo Bastida-Jumilla ◽  
Juan Morales-Sánchez ◽  
José-Luis Sancho-Gómez

1994 ◽  
Vol 111 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Robert H. Selzer ◽  
Howard N. Hodis ◽  
Helenann Kwong-Fu ◽  
Wendy J. Mack ◽  
Paul L. Lee ◽  
...  

Stroke ◽  
2011 ◽  
Vol 42 (11) ◽  
pp. 3017-3021 ◽  
Author(s):  
Joseph F. Polak ◽  
Michael J. Pencina ◽  
Daniel H. O'Leary ◽  
Ralph B. D'Agostino

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