• Ya-Chun Tang, Yuan-Chang Liu, Ming-Yi Hsu, Hui-Yu Tsai, and Chien-Ming Chen.
• Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital Linkou, 5 Fuxing Street, Kwei-Shan, Taoyuan, Taiwan 333.
• Acad Radiol. 2018 Aug 1; 25 (8): 1010-1017.

Rationale And ObjectivesWe aimed to evaluate integrated adaptive iterative dose reduction 3D (AIDR 3D) algorithm in automatic tube current modulation (ATCM) for the quantification of coronary artery calcium score (CACS) and cardiac risk stratification.Materials And MethodsA thoracic phantom with calcium inserts of known densities was scanned with filtered back projection (FBP) and AIDR 3D algorithms in small- and medium-sized phantoms. Twenty-four patients underwent two consecutive scans of CACS with FBP and AIDR 3D algorithms. The absolute Agatston score, Agatston score risk, volume score, and Agatston score percentile-based risk were compared, and concordance coefficients and agreement plots were made.ResultsAgatston and volume scores were significantly different between the phantom sizes (P < .01). There were no significant differences in the Agatston scores between FBP and AIDR 3D for the medium phantoms (P = .25). In the patients, there were no significant differences in Agatston and volume scores between FBP and AIDR 3D (P = .06 and P = .09, respectively). The correlation coefficients of Agatston and volume scores with AIDR 3D were excellent compared to those of FBP. There were no significant differences in Agatston score risk and Agatston score percentile-based risk between FBP and AIDR 3D (P = .74 and P = 1, respectively). There was mean dose reduction of 57.8% ± 18.6% for AIDR 3D.ConclusionThe absolute Agatston score differed between FBP and AIDR 3D reconstructions. However, the cardiac risk categorizations of the two methods were comparable. An integrated AIDR 3D algorithm with automatic tube current modulation enables radiation dose savings at a consistent noise level without sacrificing CACS.Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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