Impact of knowledge-based iterative model reconstruction on the feasibility of coronary computed tomography angiography in obese patients
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Gounden, Sarushen
Jeffries, Colin
Jesuthasan, Bruno
Ranjan, Shashi
Challa, Prasad
Dahiya, Arun
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Orlando, FL, USA
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Abstract
Background: Obesity is a common clinical problem that can complicate investigation of coronary artery disease (CAD). Knowledge-based iterative model reconstruction (IMR) represents a novel reconstruction technique in coronary computed tomography angiography (CCTA) with reduced radiation and improved image quality. The purpose of this study is to assess the feasibility of IMR-CCTA in patients with a Body Mass Index (BMI) ≥ 30 kg/m2. Methods: We evaluated 407 symptomatic patients between January 2015 and March 2017 undergoing CCTA on a Philips iCT 256 slice scanner with an IMR algorithm. An experienced interpreter evaluated for non-diagnostic segments, severity (>50% stenosis) and plaque morphology in a standard 16-segment model. Diagnostic scans were determined by need for additional functional or anatomical assessment due to non-definite segment severity. Logistic regression was used for data analysis. Results: Diagnostic scans were comparable between both BMI groups (89%/88%). Subgroup analysis (BMI≥30) revealed improved diagnostic ability with lower age <60 years (OR 3.7 p=0.006). Lower BMI (<30) was not associated with improved diagnostic ability (p=0.35) but resulted in lower radiation dose.Conclusion: CCTA represents an excellent modality to investigate CAD, and a knowledge-based IMR algorithm demonstrates high diagnostic ability in patients with increased BMI (≥ 30). Feasibility of diagnostic scans is also high in morbidly obese patients (BMI>40) but with increased radiation dose. Conclusion: CCTA represents an excellent modality to investigate CAD, and a knowledge-based IMR algorithm demonstrates high diagnostic ability in patients with increased BMI (≥ 30). Feasibility of diagnostic scans is also high in morbidly obese patients (BMI>40) but with increased radiation dose.
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Journal of the American College of Cardiology
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71
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11
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Cardiovascular medicine and haematology
Science & Technology
Life Sciences & Biomedicine
Cardiac & Cardiovascular Systems
Cardiovascular System & Cardiology
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Reyaldeen, R; Gounden, S; Jeffries, C; Jesuthasan, B; Ranjan, S; Challa, P; Dahiya, A, Impact of knowledge-based iterative model reconstruction on the feasibility of coronary computed tomography angiography in obese patients, Journal of the American College of Cardiology, 2018, 71 (11), pp. 1594-1594