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Effect of a calcium deblooming algorithm on accuracy of coronary computed tomography angiography
Affiliation:1. Department of Radiology, University of Cambridge, Cambridge, United Kingdom;2. Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China;3. St Pauls Hospital, Vancouver, Canada;4. GE Healthcare Technologies, Waukesha, WI, USA;1. FEops NV, Ghent, Belgium;2. The Heart Centre, Rigshospitalet, Copenhagen, Denmark;3. Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud (ICPS), Ramsay-Générale de santé, Massy, France;4. Division of Cardiology, Vancouver General Hospital, University of British Columbia, Vancouver, Canada;1. Centro Cardiologico Monzino, IRCCS, Milan, Italy;2. Department of Clinical Sciences and Community Health, Cardiovascular Section, University of Milan, Milan, Italy;3. University of Brescia, Italy;4. Department of Cardiovascular Sciences, Sapienza University, Rome, Italy;5. Department of Radiology, Azienda Ospedaliera San Giovanni Addolorata, Rome, Italy;1. Operative Unit of Radiology, G. Pasquinucci Hospital, G. Monasterio Foundation, Massa, Italy;2. Operative Unit of Cardiac Surgery, Azienda Ospedaliera Universitaria Careggi, Florence, Italy;3. Operative Unit of Cardiology, G. Pasquinucci Hospital, G. Monasterio Foundation, Massa, Italy
Abstract:BackgroundCoronary artery calcification is a significant contributor to reduced accuracy of coronary computed tomographic angiography (CTA) in the assessment of coronary artery disease severity. The aim of the current study is to assess the impact of a prototype calcium deblooming algorithm on the diagnostic accuracy of CTA.Methods40 patients referred for invasive catheter angiography underwent CTA and invasive catheter angiography. The CTA were reconstructed using a standard soft tissue kernel (CTASTAND) and a deblooming algorithm (CTADEBLOOM). CTA studies were read with and without the deblooming algorithm blinded to the invasive coronary angiogram findings. Sensitivity, specificity, accuracy, positive predictive value and negative predictive value for the detection of stenosis ≥50% or ≥70% were evaluated using quantitative coronary angiography as the reference standard. Image quality was assessed using a 5-point scale, and the presence of image artifact recorded.ResultsAll studies were diagnostic with 548 segments available for evaluation. Image score was 3.64 ± 0.72 with CTADEBLOOM, versus 3.56 ± 0.72 with CTASTAND (p = 0.38). CTADEBLOOM had significantly less calcium blooming artifact than CTASTAND (12.5% vs. 47.5%, p = 0.001). Based on a 50% stenosis threshold for defining significant disease, the Sensitivity/Specificity/PPV/NPV/Accuracy were 65.9/84.9/27.6/96.6/83.4 for CTADEBLOOM and 75.0/81.9/26.6/97.4/81.4 for CTASTAND using a ≥50% threshold. CTADEBLOOM specificity was significantly higher than CTASTAND (84.9% vs. 81.5%, p = 0.03), with no difference between the algorithms in sensitivity (p = 0.22), or accuracy (p = 0.15). These results remained unchanged when a stenosis threshold of ≥70% was used. Interobserver agreement was fair with both techniques (CTADEBLOOM k = 0.38, CTASTAND k = 0.37).ConclusionIn this proof of concept study, coronary calcification deblooming using a prototype post-processing algorithm is feasible and reduces calcium blooming with an improvement of the specificity of the CTA exam.
Keywords:Atherosclerosis  Computed tomography  Plaque  Coronary artery disease  Cardiac
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