###### Abstract  
Given the inherent characteristics of nonlinearity and nonstationarity of iterative reconstruction algorithms in computed tomography (CT) imaging, this study aimed to perform, for the first time, a voxel-based characterization of noise properties in CT imaging with the ASiR-V and ASiR algorithms as compared with conventional filtered back projection (FBP). Multiple repeated scans of the Catphan-504 phantom were carried out. CT images were reconstructed using FBP and ASiR/ASiR-V with different blending levels of reconstruction (20%, 40%, 60%, 80%, 100%). Noise maps and their nonuniformity index (_NUI_) were obtained according to the approach proposed by the report of AAPM TG-233. For the homogeneous CTR486 module, ASiR-V/ASiR allowed a noise reduction of up to 63.7%/52.9% relative to FBP. While the noise reduction values of ASiR-V/ASiR-reconstructed images ranged up to 33.8%/39.9% and 31.2%/35.5% for air and Teflon contrast objects, respectively, these values were approximately 60%/50% for other contrast objects (PMP, LDPE, polystyrene, acrylic, Delrin). Moreover, for all contrast objects but air and Teflon, ASiR-V showed a greater noise reduction potential than ASiR when the blending level was \(\geq\)40%. While noise maps of the homogenous CTP486 module showed only a slight spatial variation of noise (_NUI_ < 5.2%) for all reconstruction algorithms, the _NUI_ values of iterative-reconstructed images of the nonhomogeneous CTP404 module increased nonlinearly with blending level and were 19%/15% and 6.7% for pure ASiR-V/ASiR and FBP, respectively. Overall, these results confirm the potential of ASiR-V and ASiR in reducing noise as compared with conventional FBP, suggesting, however, that the use of pure ASiR-V or ASiR might be suboptimal for specific clinical applications. computed tomography; iterative reconstruction algorithms; ASiR; ASiR-V; noise level; noise spatial uniformity +
Footnote †: journal: Medical Physics, Pisa University Hospital \"Azienda Ospedaliero-Universitaria Pisana\", 56126 Pisa, Italy; [EMAIL_ADDRESS] (P.B. ); [EMAIL_ADDRESS] (D.M. ); [EMAIL_ADDRESS]
The introduction of iterative reconstruction (IR) algorithms in clinical practice represents an important step toward dose optimization [13; 14; 15; 16; 17; 18]. Unlike the conventional filtered back-projection (FBP) algorithm, IR algorithms take into account various physical aspects of CT image acquisition and can be based on statistical or model-based approaches [19; 20; 21; 22]. While statistical-based IR algorithms usually consider the fluctuations in the projection measurement through a statistical method (e.g., by modeling the photon counting), model-based algorithms include a more complex description of physical and optical aspects in the reconstruction process, resulting in a better representation of the whole imaging process but in a longer reconstruction time [19; 20; 21; 22]. When compared with conventional FBP, IR algorithms have proven to significantly decrease noise in CT imaging, allowing CT examinations with reduced patient exposure while providing still acceptable diagnostic images [23; 24; 25; 26; 27; 28]. The noise properties of CT images obtained using IR algorithms can be rather different from those of FBP-derived CT images [20; 21]. Indeed, IR algorithms can have an impact not only on the noise level but also on the noise texture of CT images [24; 29; 30; 31; 32; 33; 34; 35]. Therefore, for each specific IR algorithm, a comprehensive characterization of the noise properties and quality of reconstructed CT images is recommended to adequately assess its dose reduction potential and usefulness. So far, a number of IR algorithms with different characteristics have been implemented on clinical CT scanners [21; 22], such as the adaptive statistical iterative reconstruction (ASiR) [36], adaptive statistical iterative reconstruction-V (ASiR-V) [37], and Vee [38] (GE Healthcare, Waukesha, WI, USA).