Adaptive Statistical Iterative Reconstruction (ASIR): Re-defining CT dose reduction strategies

Abstract

KEY LEARNING OBJECTIVES: (1) Brief description of ASIR (Adaptive Statistical Iterative Reconstruction) physics. (2) Compare diagnostic quality of CT scan images performed without and with ASIR. (3) Demonstrate various clinical applications of ASIR. DESCRIPTION: Diagnostic x-rays account for the largest artificial source of exposure to ionizing radiation and CT represents the greater proportion. Traditionally, reducing CT dose result in an increase in image noise and a compromise on image quality. ASIR, on the other hand utilizes complex algebraic calculations to lower image noise and CT dose without loss of anatomical detail. ASIR has been shown to reduce CT doses by up to 50%. A study conducted in our institution comparing the Dose Length Products (DLPs) of CT pulmonary angiogram scans performed in the same patients without and with ASIR showed statistically significant reduction in dose of up to 42% without compromising diagnostic accuracy (445.87 vs 257.59). This educational poster provides a brief description of how ASIR works. It also shows the diagnostic quality of images obtained with ASIR by comparing similar images of the same patients without ASIR. Thirdly, the various ways in which ASIR can be utilized will be discussed. CONCLUSION: ASIR effectively lowers CT doses without compromising diagnostic quality. Radiologists need to be conversant with recent developments in CT dose lowering strategies such as ASIR and various ways in which it can be utilized clinically.