Contrast agent distribution in the lumen and wall of the abdominal aorta according to CT-angiographic study data

An approach to the approximation and analysis of the CT density signal component associated with intravascular radiocontrast agent (RCA) based on computed tomography angiography (CTA) images of the abdominal aorta is presented. The aim of the work is to study the possibility of extracting and analyzing the RCA-induced component in the lumen and wall of the abdominal aorta on the CTA image. A functionality for describing one-dimensional and two-dimensional distribution of the CTA as a set of sums of sigmoid of a special type is proposed. The nonlinear least squares method with Levenberg – Marquardt optimization is used for approximation. The algorithm is tested on an open data set consisting of 594 CTA images. Data preparation is performed using specialized software Slicer 3D. The results demonstrate the absence of statistically significant differences in the CTA density values between the original images and the approximation results (p> 0.05, paired Wilcoxon test). The sensitivity of the model to different distributions of the RCA in the area of aneurysm, thrombosis and origin of the main arteries is demonstrated. Sensitivity is defined as the presence of statistically significant differences in the calculated parameters of the model for the area of homogeneous and non-homogeneous distribution of the RCA within each of the CT studies. The values of the root-mean-square approximation error for the specified areas do not differ statistically significantly and are unimodally distributed (p > 0.7) within a single CT study. The proposed approach can be useful for personalizing CTA, developing algorithms for processing CTA data, synthesizing non-contrast CT data, and training artificial intelligence algorithms.