Purpose: Multidetector CT Coronary Angiography (MDCT-CA) allows the quantification of coronary artery stenosis with a high level of accuracy; however better estimation of stenosis can be achieved using appropriate reformatting filters, especially in stents and calcified segments. Quantitative Computed vessel analysis (QCTA) is intended to overcome these limits. The aim of the study is to evaluate the accuracy of QCTA with different filters in comparison to quantitative coronary angiography (QCA) and visual score. Methods and Materials: Two blinded operators visually scored 17 consecutive patients referred for MDCT-CA with a per-segment analysis. The degree of stenosis was classified as 0-20%, 20-50% (wall irregularities), 50-70% (significant disease), 70-100% (occlusion of the vessel). Each segment was analysed using electronic callipers of the QCTA system with 15 different filters. No editing of the contours was performed. Data were compared to QCA. Comparison between QCTA results, visual score and QCA were performed by means of Spearman rank correlation. Results: From a total of 25 segments (mean 1,4 diseased segment per patient) analysed 375 measurements were considered. Good correlation was found between Visual score and QCA (rho=0.852; p<0.0001) and between QCA and CA (rho=0.804; p<0.0001). Moderate correlation was found between QCA and QCTA only using 2 filters (rho=0.444; p<0.0001 for YA filter and rho=0.450; p<0.0001 for YB filter). Conclusions: Overall accuracy of QCTA is low if editing of the contours is not applied especially in calcified vessels. Particular filters can help to better estimate the exact percentage of stenosis.
Comparison between different kernel reformatting filters in 3D quantitative analysis of mdct coronary angiography
MALAGO', Roberto;POZZI MUCELLI, Roberto
2011-01-01
Abstract
Purpose: Multidetector CT Coronary Angiography (MDCT-CA) allows the quantification of coronary artery stenosis with a high level of accuracy; however better estimation of stenosis can be achieved using appropriate reformatting filters, especially in stents and calcified segments. Quantitative Computed vessel analysis (QCTA) is intended to overcome these limits. The aim of the study is to evaluate the accuracy of QCTA with different filters in comparison to quantitative coronary angiography (QCA) and visual score. Methods and Materials: Two blinded operators visually scored 17 consecutive patients referred for MDCT-CA with a per-segment analysis. The degree of stenosis was classified as 0-20%, 20-50% (wall irregularities), 50-70% (significant disease), 70-100% (occlusion of the vessel). Each segment was analysed using electronic callipers of the QCTA system with 15 different filters. No editing of the contours was performed. Data were compared to QCA. Comparison between QCTA results, visual score and QCA were performed by means of Spearman rank correlation. Results: From a total of 25 segments (mean 1,4 diseased segment per patient) analysed 375 measurements were considered. Good correlation was found between Visual score and QCA (rho=0.852; p<0.0001) and between QCA and CA (rho=0.804; p<0.0001). Moderate correlation was found between QCA and QCTA only using 2 filters (rho=0.444; p<0.0001 for YA filter and rho=0.450; p<0.0001 for YB filter). Conclusions: Overall accuracy of QCTA is low if editing of the contours is not applied especially in calcified vessels. Particular filters can help to better estimate the exact percentage of stenosis.
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