PURPOSE: To evaluate the accuracy and effect on interreader reproducibility of automated versus manual volumetric quantification of noncalcified coronary artery plaque burden at coronary computed tomography angiography. MATERIALS AND METHODS: Thirty-seven patients underwent 64-slice coronary computed tomography angiography. Two experienced observers in consensus evaluated each study and identified 40 noncalcified coronary artery plaques. Also in consensus, they performed manual, 3-dimensional planimetric measurements on each plaque as the reference standard. The same 2 observers then performed volumetric measurements on each plaque using a threshold-based automated volumetry automated plaque analysis algorithm. Two different, less experienced observers also performed both, manual and automated measurements of each plaque, first independently and then in consensus. Spearman rank correlation was used to determine association between variables. RESULTS: Automated volumetry was successfully performed on each plaque. There was excellent (R=0.920) correlation between the expert manual measurements (average plaque burden=33.58 mm(3)+/-18.16) and automated plaque volumetry (35.64 mm(3)+/-16.42). For the less experienced observers, there was better correlation with expert manual measurements using automated plaque volumetry (R=0.885) than with manual measurements (R=0.854). Interreader correlation for volume measurements by the 2 less experienced observers without and with use of the automated plaque analysis algorithm significantly (P<0.001) increased from R=0.781 to R=0.919. CONCLUSIONS: Compared with expert manual measurements, automated plaque volumetry enables accurate quantification of noncalcified plaque burden. Reproducibility of plaque measurements between different observers is improved. Use of such automated plaque analysis algorithms should facilitate fast, objective and reproducible assessment of noncalcified plaque burden for risk stratification and therapeutic monitoring.
PURPOSE: To evaluate the accuracy and effect on interreader reproducibility of automated versus manual volumetric quantification of noncalcified coronary artery plaque burden at coronary computed tomography angiography. MATERIALS AND METHODS: Thirty-seven patients underwent 64-slice coronary computed tomography angiography. Two experienced observers in consensus evaluated each study and identified 40 noncalcified coronary artery plaques. Also in consensus, they performed manual, 3-dimensional planimetric measurements on each plaque as the reference standard. The same 2 observers then performed volumetric measurements on each plaque using a threshold-based automated volumetry automated plaque analysis algorithm. Two different, less experienced observers also performed both, manual and automated measurements of each plaque, first independently and then in consensus. Spearman rank correlation was used to determine association between variables. RESULTS: Automated volumetry was successfully performed on each plaque. There was excellent (R=0.920) correlation between the expert manual measurements (average plaque burden=33.58 mm(3)+/-18.16) and automated plaque volumetry (35.64 mm(3)+/-16.42). For the less experienced observers, there was better correlation with expert manual measurements using automated plaque volumetry (R=0.885) than with manual measurements (R=0.854). Interreader correlation for volume measurements by the 2 less experienced observers without and with use of the automated plaque analysis algorithm significantly (P<0.001) increased from R=0.781 to R=0.919. CONCLUSIONS: Compared with expert manual measurements, automated plaque volumetry enables accurate quantification of noncalcified plaque burden. Reproducibility of plaque measurements between different observers is improved. Use of such automated plaque analysis algorithms should facilitate fast, objective and reproducible assessment of noncalcified plaque burden for risk stratification and therapeutic monitoring.
Authors: Min Su Lee; Eun Ju Chun; Kil Joong Kim; Jeong A Kim; Mani Vembar; Sang Il Choi Journal: Int J Cardiovasc Imaging Date: 2010-10-06 Impact factor: 2.357
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Authors: Junjie Yang; Guanhua Dou; Christian Tesche; Carlo N De Cecco; Brian E Jacobs; U Joseph Schoepf; Yundai Chen Journal: BMC Cardiovasc Disord Date: 2019-02-11 Impact factor: 2.298