INTRODUCTION: We aimed to develop an automated algorithm (APQ) for accurate volumetric quantification of non-calcified (NCP) and calcified plaque (CP) from coronary CT angiography (CCTA). METHODS: APQ determines scan-specific attenuation thresholds for lumen, NCP, CP and epicardial fat, and applies knowledge-based segmentation and modeling of coronary arteries, to define NCP and CP components in 3D. We tested APQ in 29 plaques for 24 consecutive scans, acquired with dual-source CT scanner. APQ results were compared to volumes obtained by manual slice-by-slice NCP/CP definition and by interactive adjustment of plaque thresholds (ITA) by 2 independent experts. RESULTS: APQ analysis time was <2 sec per lesion. There was strong correlation between the 2 readers for manual quantification (r = 0.99, p < 0.0001 for NCP; r = 0.85, p < 0.0001 for CP). The mean HU determined by APQ was 419 +/- 78 for luminal contrast at mid-lesion, 227 +/- 40 for NCP upper threshold, and 511 +/- 80 for the CP lower threshold. APQ showed a significantly lower absolute difference (26.7 mm(3) vs. 42.1 mm(3), p = 0.01), lower bias than ITA (32.6 mm(3) vs 64.4 mm(3), p = 0.01) for NCP. There was strong correlation between APQ and readers (R = 0.94, p < 0.0001 for NCP volumes; R = 0.88, p < 0.0001, for CP volumes; R = 0.90, p < 0.0001 for NCP and CP composition). CONCLUSIONS: We developed a fast automated algorithm for quantification of NCP and CP from CCTA, which is in close agreement with expert manual quantification. Copyright (c) 2009 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
INTRODUCTION: We aimed to develop an automated algorithm (APQ) for accurate volumetric quantification of non-calcified (NCP) and calcified plaque (CP) from coronary CT angiography (CCTA). METHODS:APQ determines scan-specific attenuation thresholds for lumen, NCP, CP and epicardial fat, and applies knowledge-based segmentation and modeling of coronary arteries, to define NCP and CP components in 3D. We tested APQ in 29 plaques for 24 consecutive scans, acquired with dual-source CT scanner. APQ results were compared to volumes obtained by manual slice-by-slice NCP/CP definition and by interactive adjustment of plaque thresholds (ITA) by 2 independent experts. RESULTS:APQ analysis time was <2 sec per lesion. There was strong correlation between the 2 readers for manual quantification (r = 0.99, p < 0.0001 for NCP; r = 0.85, p < 0.0001 for CP). The mean HU determined by APQ was 419 +/- 78 for luminal contrast at mid-lesion, 227 +/- 40 for NCP upper threshold, and 511 +/- 80 for the CP lower threshold. APQ showed a significantly lower absolute difference (26.7 mm(3) vs. 42.1 mm(3), p = 0.01), lower bias than ITA (32.6 mm(3) vs 64.4 mm(3), p = 0.01) for NCP. There was strong correlation between APQ and readers (R = 0.94, p < 0.0001 for NCP volumes; R = 0.88, p < 0.0001, for CP volumes; R = 0.90, p < 0.0001 for NCP and CP composition). CONCLUSIONS: We developed a fast automated algorithm for quantification of NCP and CP from CCTA, which is in close agreement with expert manual quantification. Copyright (c) 2009 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
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