Impact of a prototype, dedicated AI-based spectral image reconstruction algorithm on the quality of low-keV virtual...

Recently, CT manufacturers have developed deep-learning-based reconstruction (DLR) algorithms for conventional and spectral CT images. On dual-energy CT platforms, DLR algorithms have been developed in particular to reduce image noise in virtual monoenergetic images (VMIs), and to improve the accuracy of iodine concentrations on iodine maps.

To assess the impact of a prototype, dedicated Spectral AI Reconstruction (SAIR) algorithm (Spectral Precise Image; Philips Healthcare) compared with a hybrid iterative reconstruction (HIR) algorithm ("Spectral", Philips Healthcare) on the quality of low-keV VMIs and iodine maps in abdomen-pelvis CT conditions.

A spectral phantom was scanned on the dual-layer spectral CT system at 120 kVp and a CTDI_vol of 12 mGy. VMIs at 40/50/60/70 keV were generated using Level 4 of HIR algorithm and the five levels of SAIR algorithm named Smoother/Smooth/Standard/Sharp/Sharper. Noise power spectrum (NPS) was computed to assess noise magnitude and noise texture (f_av). Task-based transfer function (TTF) was calculated to assess spatial resolution (f₅₀) on blood-mimicking material plus iodine inserts at 2 and 4 mg/mL. A detectability index (d') was computed to model the detection task of two contrast-enhanced lesion according to keV. The accuracy of the iodine concentrations measured from six iodine inserts was calculated on iodine maps for HIR and all SAIR levels.

For all keV, noise magnitude values were higher than with HIR using the Sharp (11.9 ± 5.6%; p > 0.05) and Sharper (39.3 ± 7.3%; p = 0.004) levels and lower than HIR for the other SAIR levels, decreasing from Standard (-15.3 ± 3.9%; p > 0.05) to Smooth (-42.3 ± 2.2%; p = 0.004) and Smoother levels (-70.5 ± 1.1%; p < 0.001). For all energy levels, f_av values were higher with all SAIR levels than with HIR, except when using the Smoother level. For both inserts, differences in f₅₀ values between the five SAIR levels and HIR did not exceed ± 0.05 mm^-1. For all energy levels and both simulated lesions, d' values were only higher than with HIR when using the Standard (32.4 ± 7.5%; p > 0.05), Smooth (95.6 ± 10.1%; p = 0.008) and Smoother (303.4 ± 16.6%; p < 0.001) levels. The accuracy of measured iodine values, calculated for each type of reconstruction, was similar (p > 0.05) and equal to 0.25 ± 0.03 mg/mL.

Compared to the HIR algorithm used in clinical practice for low-keV VMIs, Standard, Smooth and Smoother levels of SAIR reduced image noise and improved the detectability of contrast-enhanced lesions. Better noise texture was found only with the Standard and Smooth levels compared to HIR.