IMAGE QUALITY IN ABDOMINAL CT: A COMPARISON OF TWO RECONSTRUCTION ALGORITHMS IN FILTERED BACK PROJECTION (FBP)

Abstract

Objectives: The aim of this study was to evaluate the effect of the choice of kernel on the image quality in abdominal CT images with focus on liver lesion visibility.

Methods: In this comparative study 84 abdominal CT examinations of patients with liver lesions that included parallel series reconstructed with two different kernels (B30 and B45) were analyzed. The subjective assessment of image quality was performed using visual grading analysis based on anatomical criteria, liver lesion visibility and perceived image quality. Objective image quality was assessed by measurements of Hounsfield unit (HU) values (average and standard deviation) in abdominal organs and calculations of contrast-to-noise ratios (CNR).

Results: B30 kernel performed significantly better than B45 in all criteria except for sharpness. The most considerable improvement of the image quality was in terms of subjective experienced image noise, overall diagnostic image quality and visually sharp reproduction of liver lesions. The physical measurements showed that CNR increased by up to 46% when using B30.

Conclusions: Using a B30 kernel algorithm for image reconstruction reduces noise and by that improves image quality and diagnostic accuracy significantly when compared to B45.