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.
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.
Authors: Luca Saba; Pankaj K Jain; Harman S Suri; Nobutaka Ikeda; Tadashi Araki; Bikesh K Singh; Andrew Nicolaides; Shoaib Shafique; Ajay Gupta; John R Laird; Jasjit S Suri Journal: J Med Syst Date: 2017-05-13 Impact factor: 4.460
Authors: Pierleone Lucatelli; Eytan Raz; Luca Saba; Giovanni Maria Argiolas; Roberto Montisci; Max Wintermark; Kevin S King; Filippo Molinari; Nobutaka Ikeda; Paolo Siotto; Jasjit S Suri Journal: Eur Radiol Date: 2016-03-30 Impact factor: 5.315
Authors: Pankaj K Jain; Neeraj Sharma; Luca Saba; Kosmas I Paraskevas; Mandeep K Kalra; Amer Johri; John R Laird; Andrew N Nicolaides; Jasjit S Suri Journal: Diagnostics (Basel) Date: 2021-12-02