Knowledge-based iterative model reconstruction: Comparative image quality with low tube voltage cerebral CT angiography

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Abstract

The aim of this study was to compare image quality of low tube voltage cerebral computed tomography angiography (CTA) reconstructed with knowledge-based iterative model reconstruction (IMR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR).

A total of 101 patients with suspected cerebrovascular diseases were enrolled and randomized into 2 groups, 100 kVp tube voltage (n = 53) and reduced tube voltage (80 kVp) (n = 48). Computed tomography data were reconstructed with IMR, FBP, and HIR algorithms. The image noise, vascular attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured and calculated. Two blinded radiologists independently evaluated image quality based on diagnostic confidence on a 3-point scale. Quantitative and qualitative assessments were compared between different groups and reconstruction subgroups.

Vascular attenuation was higher in the reduced tube voltage group than in 100-kVp tube voltage group, but showed no significant difference within each group. In both groups, the image noise, vascular SNR, and CNR were significantly improved by IMR as compared with FBP and HIR. Inter-group comparison indicated that IMR with reduced tube voltage showed better image quality with lower image noise and higher vascular SNR and CNR than FBP and HIR at 100 kVp, but slightly inferior to IMR at 100 kVp. IMR also yields the best qualitative image quality, and improves the diagnostic confidence of atherosclerosis and aneurysm. Compared with the standard 120-kVp protocol (1.86mSv), the radiation doses of 100 kVp (1.13mSv) and 80 kVp (0.56mSv) were 39% and 70% less, respectively.

The quantitative and qualitative image quality obtained by IMR was superior to that obtained by FBP and HIR for low tube voltage cerebral CTA.

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