Purpose: To compare the quantitative and qualitative image quality of hybrid (HBIR) and model based (MBIR) iterative reconstruction during coronary Computed Tomography Angiography (CTA). Materials and Methods: Institutional review board approved this retrospective study. Patients (n=200) underwent a single coronary CTA with two iterative reconstruction techniques. Group A employed HBIR and group B employed MBIR. Quantitative and qualitative image quality was compared for each group. The mean attenuation values and signal-to-noise ratio (SNR) of each group were compared. Visual grading characteristics (VGC) and Cohen’s Kappa methodology were measured employing an image quality scoring system for coronary CTA. Receiver operating (JAFROC) and stenosis severity were compared with conventional coronary angiography. A p-value <0.05 was considered statistically significant. Results: Mean attenuation values (HU) in the HBIR group were significantly greater in the cusp (564.18±118.71) and left coronary (517.59±118.63) whilst in the MBIR group, the right coronary (531.67±138.93), left anterior descending (529.82±120.6) and left circumflex (538.32±132.94) arteries were significantly higher (p<0.001). The SNR was significantly greater in MBIR (5.32±1.1) compared to HBIR (3.64±0.8) (p<0.0001), with MBIR being superior to HBIR in the total and individual segments of the coronary arteries. VGC image quality assessment demonstrated that readers preferred HBIR over MBIR (p<0.001). Analysis of JAFROC data demonstrated a significant difference in detection of coronary stenosis in RCA (p<0.021), LCA (p<0.0001) and LD (p<0.0001) with HBIR showing overall smaller variability range compared to MBIR. Conclusion: When comparing quantitative and qualitative image quality, MBIR was superior in the former, whilst HBIR was superior in the later. Coronary artery stenosis assessment demonstrated less variability in diagnosis when using HBIR compared to MBIR. This highlights the need for careful attention when employing iterative reconstruction in order not to impact clinical outcomes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.