학술논문
Effect of a calcium deblooming algorithm on accuracy of coronary computed tomography angiography.
Document Type
Academic Journal
Author
Weir-McCall JR; Department of Radiology, University of Cambridge, Cambridge, United Kingdom.; Wang R; Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.; Halankar J; St Pauls Hospital, Vancouver, Canada.; Hsieh J; GE Healthcare Technologies, Waukesha, WI, USA.; Hague CJ; St Pauls Hospital, Vancouver, Canada.; Rosenblatt S; St Pauls Hospital, Vancouver, Canada.; Fan Z; Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.; Sellers SL; St Pauls Hospital, Vancouver, Canada.; Murphy DT; St Pauls Hospital, Vancouver, Canada.; Blanke P; St Pauls Hospital, Vancouver, Canada.; Xu L; Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China. Electronic address: leixu2001@hotmail.com.; Leipsic JA; St Pauls Hospital, Vancouver, Canada.
Source
Publisher: Elsevier Country of Publication: United States NLM ID: 101308347 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-861X (Electronic) Linking ISSN: 1876861X NLM ISO Abbreviation: J Cardiovasc Comput Tomogr Subsets: MEDLINE
Subject
Language
English
Abstract
Background: Coronary 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.
Methods: 40 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 (CTA DEBLOOM ). 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.
Results: All studies were diagnostic with 548 segments available for evaluation. Image score was 3.64 ± 0.72 with CTADEBLOOM , versus 3.56 ± 0.72 with CTA STAND (p = 0.38). CTA DEBLOOM had significantly less calcium blooming artifact than CTA STAND (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 CTA DEBLOOM and 75.0/81.9/26.6/97.4/81.4 for CTA STAND using a ≥50% threshold. CTA DEBLOOM specificity was significantly higher than CTA STAND (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 (CTA DEBLOOM k = 0.38, CTA STAND k = 0.37).
Conclusion: In 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.
(Copyright © 2020. Published by Elsevier Inc.)
Methods: 40 patients referred for invasive catheter angiography underwent CTA and invasive catheter angiography. The CTA were reconstructed using a standard soft tissue kernel (CTA
Results: All studies were diagnostic with 548 segments available for evaluation. Image score was 3.64 ± 0.72 with CTA
Conclusion: In 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.
(Copyright © 2020. Published by Elsevier Inc.)