Accuracy and Precision of Iodine Quantification in Subtracted Micro-Computed Tomography: Effect of Reconstruction and Noise Removal Algorithms

Abstract

Purpose: To evaluate the effect of reconstruction and noise removal algorithms on the accuracy and precision of iodine concentration (C_I) quantified with subtracted micro-computed tomography (micro-CT).

Procedures: Two reconstruction algorithms were evaluated: a filtered backprojection (FBP) algorithm and a simultaneous iterative reconstruction technique (SIRT) algorithm. A 3D bilateral filter (BF) was used for noise removal. A phantom study evaluated and compared the image quality, and the accuracy and precision of C_I in four scenarios: filtered FBP, filtered SIRT, non-filtered FBP, and non-filtered SIRT. In vivo experiments were performed in an animal model of chemically-induced mammary cancer.

Results: Linear relationships between the measured and nominal C_I values were found for all the scenarios in the phantom study (R² > 0.95). SIRT significantly improved the accuracy and precision of C_I compared to FBP, as given by their lower bias (adj. p-value = 0.0308) and repeatability coefficient (adj. p-value < 0.0001). Noise removal enabled a significant decrease in bias in filtered SIRT images only; non-significant differences were found for the repeatability coefficient. The phantom and in vivo studies showed that C_I is a reproducible imaging parameter for all the scenarios (Pearson r > 0.99, p-value < 0.001). The contrast-to-noise ratio showed non-significant differences among the evaluated scenarios in the phantom study, while a significant improvement was found in the in vivo study when SIRT and BF algorithms were used.

Conclusions: SIRT and BF algorithms improved the accuracy and precision of C_I compared to FBP and non-filtered images, which encourages their use in subtracted micro-CT imaging.

Keywords: Accuracy; Bilateral filter; Iodine concentration; Iterative reconstruction; Micro-CT; Precision; Quantitative imaging; SIRT.