Key result
Automated and semiautomated algorithms for carotid intima-media thickness analysis showed a strong correlation (Pearson ρ = 0.9; 95% CI, 0.82-0.95; P = 0.0001).
Why the study?
Do automated algorithms correlate with semiautomated and manual methods for analyzing carotid artery wall thickness and intima-media thickness on CT and sonography?
Cross-Sectional (n=20)
Do automated algorithms correlate with semiautomated and manual methods for analyzing carotid artery wall thickness and intima-media thickness on CT and sonography?
Effect estimate: Pearson ρ = 0.9 (95% CI 0.82-0.95)
p-value: p=0.0001
May support automated carotid IMT tools in research; leaves open prospective outcome validation before clinical use.
OBJECTIVES: The purpose of this study was to compare automated and semiautomated algorithms for analysis of carotid artery wall thickness and intima-media thickness on multidetector row computed tomographic (CT) angiography and sonography, respectively, and to study the correlation between them. METHODS: Twenty consecutive patients underwent multidetector row CT angiographic and sonographic analysis of carotid arteries (mean age, 66 years; age range, 59-79 years). The intima-media thickness of the 40 carotid arteries was measured with novel and dedicated automated software analysis and by 4 observers who manually calculated the intima-media thickness. The carotid artery wall thickness was automatically estimated by using a specific algorithm and was also semiautomatically quantified. The correlation between groups was calculated by using the Pearson ρ statistic, and scatterplots were calculated. We evaluated intermethod agreement using Bland-Altman analysis. RESULTS: By comparing automated carotid artery wall thickness, automated intima-media thickness, semiautomated carotid artery wall thickness, and semiautomated intima-media thickness analyses, a statistically significant association was found, with the highest values obtained for the association between semiautomated and automated intima-media thickness analyses(Pearson ρ = 0.9; 95% confidence interval, 0.82-0.95; P = 0.0001). The lowest values were obtained for the association between semiautomated intima-media thickness and automated carotid artery wall thickness analyses (Pearson ρ = 0.44; 95% confidence interval, 0.15-0.66; P = 0.0047). In the Bland-Altman analysis, the better results were obtained by comparing the semiautomated and automated algorithms for the study of intima-media thickness, with an interval of -16.1% to +43.6%. CONCLUSIONS: The results of this preliminary study showed that carotid artery wall thickness and intima-media thickness can be studied with automated software, although the CT analysis needs to be further improved.
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Saba et al. (2013) conducted a cross-sectional in Carotid artery evaluation (n=20). Automated algorithms for carotid artery analysis vs. Semiautomated algorithms was evaluated on Correlation between automated and semiautomated intima-media thickness analyses (Pearson ρ = 0.9, 95% CI 0.82-0.95, p=0.0001). Automated and semiautomated algorithms for carotid intima-media thickness analysis showed a strong correlation (Pearson ρ = 0.9; 95% CI, 0.82-0.95; P = 0.0001).
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