Abstract
BackgroundFiltered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) are ubiquitously applied in the reconstruction of coronary CT angiography (CCTA) datasets. However, currently no data is available on the impact of a model-based adaptive filter (MBAF2), recently developed for a dedicated cardiac scanner. PurposeOur aim was to determine the effect of MBAF2 on subjective and objective image quality parameters of coronary arteries on CCTA. MethodsImages of 102 consecutive patients referred for CCTA were evaluated. Four reconstructions of coronary images (FBP, ASIR, MBAF2, ASIR + MBAF2) were co-registered and cross-section were assessed for qualitative (graininess, sharpness, overall image quality) and quantitative [image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] image quality parameters. Image noise and signal were measured in the aortic root and the left main coronary artery, respectively. Graininess, sharpness, and overall image quality was assessed on a 4-point Likert scale. ResultsAs compared to FBP, ASIR, and MBAF2, ASIR + MBAF2 resulted in reduced image noise [53.1 ± 12.3, 30.6 ± 8.5, 36.3 ± 4.2, 26.3 ± 4.0 Hounsfield units (HU), respectively; p < 0.001], improved SNR (8.4 ± 2.6, 14.1 ± 3.6, 11.8 ± 2.3, 16.3 ± 3.3 HU, respectively; p < 0.001) and CNR (9.4 ± 2.7, 15.9 ± 4.0, 13.3 ± 2.5, 18.3 ± 3.5 HU, respectively; p < 0.001). No difference in sharpness was observed amongst the reconstructions (p = 0.08). Although ASIR + MBAF2 was non-superior to ASIR regarding overall image quality (p = 0.99), it performed better than FBP (p < 0.001) and MBAF2 (p < 0.001) alone. ConclusionThe combination of ASIR and MBAF2 resulted in reduced image noise and improved SNR and CNR. The implementation of MBAF2 in clinical practice may result in improved noise reduction performance and could potentiate radiation dose reduction.
Highlights
Coronary CT angiography (CCTA) is a robust, non-invasive tool that is well established for the assessment of coronary artery disease (CAD)
Our study revealed that MBAF2, combined with adaptive statistical iterative reconstruction (ASIR) performs better than Filtered back projection (FBP), ASIR, and MBAF2 alone, in all examined quantitative image quality parameters
It is essential to emphasize that the utilization of ASIR resulted in reduced subjective and objective image noise as compared to MBAF2 alone
Summary
Coronary CT angiography (CCTA) is a robust, non-invasive tool that is well established for the assessment of coronary artery disease (CAD). The world’s first dedicated cardiovascular CT scanner (Cardio Graphe, GE Healthcare, Chicago, USA) was introduced in 2017. This purpose-built cardiovascular scanner is optimized for the visualization of the entire heart and coronary system in a single heartbeat with 140 mm coverage at a rotation speed of 0.24 sec per rotation [5]. Several iterative reconstruction (IR) algorithms have become available on CT platforms to reduce radiation exposure of CCTA, while maintaining or even improving contrast-to-noise (CNR) and signal-to-noise ratio (SNR). Developed as an alternative to filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR) has resulted in reduced image noise and improved quality of CCTA images [6]. Model-based adaptive filter (MBAF2) has been introduced as a novel algorithm for CCTA datasets. In order to achieve this, we compared the image quality of datasets reconstructed using FBP, ASIR, MBAF2, and the combination of ASIR and MBAF2
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