Noise-Optimized Virtual Monoenergetic Reconstruction Technique in Dual-Energy CT for Planning of Transcatheter Aortic Valve Replacement

Objectives: To evaluate objective and subjective image quality parameters of images reconstructed using a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique in dual-energy computed tomography (DECT) angiography for planning of transcatheter aortic valve replacement (TAVR).
Methods: Datasets of 47 patients (35 men; 64.1 ± 10.9 years) who underwent DECT angiography of heart and vascular access prior to TAVR were reconstructed with standard linear blending (F_0.5), VMI+, and traditional monoenergetic (VMI) algorithms in 10-keV intervals from 40-100 keV. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 564 arterial segments were evaluated. Subjective analysis was rated by three blinded observers using a Likert scale.
Results: Mean SNR and CNR were highest in 40 keV VMI+ series (SNR, 27.8 ± 13.0; CNR, 26.3 ± 12.7), significantly (all p < 0.001) superior to all VMI series, which showed highest values at 70 keV (SNR, 18.5 ± 7.6; CNR, 16.0 ± 7.4), as well as linearly-blended F_0.5 series (SNR, 16.8 ± 7.3; CNR, 13.6 ± 6.9). Highest subjective image quality scores were observed for 40, 50, and 60 keV VMI+ reconstructions (all p > 0.05), significantly superior to all VMI and standard linearly-blended images (all p < 0.01).
Conclusions: VMI+ reconstructions at low keV levels can significantly increase objective image quality compared to VMI and standard linear-blending image reconstruction and improve subjective image quality in preprocedural DECT angiography for TAVR planning purposes.