Does Iterative Reconstruction Improve Image Quality and Reduce Dose in Computed Tomography?

Abstract

The Filtered Back Projection (FBP) algorithm has been the standard algorithm for image reconstruction in computed tomography (CT) for many years, but it creates possible streak artifacts and a notable increase in image noise when radiation dose is reduced exceedingly. With 
technological advancement and increased computational capacities in workstations, iterative 
reconstruction (IR) algorithms have re-emerged as a potential alternative. The purpose of this 
review is to establish if there is a general consensus that IR algorithms faithfully reduce radiation dose and improve image quality in CT in comparison with the FBP algorithm. A systematic 
review of the literature from 2012 to 2015 was conducted using Ovid MEDLINE and PubMed 
databases, as well as various well-known journals such as the American Journal of Roentgenology, European Journal of Radiology, Physica Medica and the Korean Journal of Radiology. 
A total of 57 articles were categorized as either synopsis articles or performance evaluation 
clinical studies, where the latter was further divided into 6 sub-categories according to the type 
of IR algorithm examined. The results show that the use of IR algorithms reduces objective 
image noise, and at least preserves spatial resolution and low contrast detectability, even when 
dose is reduced. The findings are also applicable to specific patient groups, such as pediatrics 
and obese patients. In conclusion, there is a general consensus that IR algorithms can faithfully 
reduce radiation dose and improve image quality in CT in comparison with the FBP algorithm.