The Influence of Adaptive Statistical Iterative Reconstruction Algorithm on Image Quality and Volume CT Dose Index in Head CT Scan Compared To Filtered Back Projection

This study aimed to compare the image quality and volume dose index of head CT scan between two adaptive statistical iterative reconstructions (ASIR) and the filtered back projection (FBP) algorithms. CT number, noise and signal to noise ratio(SNR) for white matter(WM), gray matter(WM), cerebrospinal fluid(CSF( and skull bone were investigated in brain CT scans of 60 patients. All images were reconstructed by FBP and ASIR 40% algorithms. A water phantom was also used to compare the average CT number; noise, signal-to-noise (SNR), and contrast-to-noise ratio (CNR) between algorithms under different acquisition parameters. Volume computed tomography dose index (CTDIvol) and (dose-length product) DLP were obtained from scanner software. Data were analyzed by T-test and Mann-Whitney statistical test with a significance level of less than 0.05. Image noise of gray matter, CSF and skull bone was significantly lower for ASIR algorithm (P<0.05). The difference in SNR for white matter and gray matter was not significant between the two algorithms but it was higher for CSF and bone for ASIR. In phantom study, Image noise, CTDIvol and DLP in both axial and spiral scan modes were higher for FBP algorithm (P<0.05). In addition, there was no significant difference in SNR and CNR between the two algorithms (P>0.05). ASIR algorithm reduces the dose and image noise in head CT scan compared to the filtered back projection. In addition, using ASIR algorithm the image noise does not increase with lower mA.