Iterative reconstruction

objectiveTo compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithms.

methods46 patients undergoing low-dose lower-extremity CTA were enrolled. Images were reconstructed using ASIR-V (blending factor of 50% (AV-50) and 100% (AV-100)) and DLIR (medium (DL-M), and high (DL-H)). CT values and standard deviation of the aorta, psoas, popliteal artery, popliteal and ankle muscles were measured. The edge-rise distance and edge-rise slope were calculated. The degrees of granularity and edge blurring were assessed using a 5-point scale. The stenosis degrees were measured on the four reconstructions, and their mean square errors against that of digital subtraction angiography were calculated and compared.

resultsFor both ASIR-V and DLIR, higher reconstruction intensity generated lower noise and higher signal-to-noise ratio and contrast-to-noise ratio values. The standard deviation values in AV-100 images were significantly lower than other reconstructions. The two DLIR image groups had higher edge-rise slope and lower edge-rise distance (DL-M:1.79 ± 0.37 mm and DL-H:1.82 ± 0.38 mm

conclusionDLIR images had higher image quality ratings with lower image noise and sharper vessel walls in low-dose lower-extremity CTA, and DL-H provides the best overall image quality and highest accuracy in diagnosing artery stenoses. ADVANCES IN KNOWLEDGE: DLIR provides high-quality images with sharper edges compared to ASIR-V during low-dose CTA of lower extremity arteries, and DLIR (high) provides the best overall image quality and highest accuracy in diagnosing artery stenoses among all reconstruction algorithms (ASIR-V and DLIR). ASIR-V with blending factor of 100% has the strongest noise reduction ability among all reconstruction algorithms (ASIR-V and DLIR); however, it generates the most blurred images.