Iodine Images in Dual-energy CT: Detection of Hepatic Steatosis by Quantitative Iodine Concentration Values.
Stefanie BeckLaurenz JahnDominik DeniffelIsabelle RiedererAndreas SauterMarcus R MakowskiDaniela PfeifferPublished in: Journal of digital imaging (2022)
Hepatic steatosis is a common condition and an early manifestation of a systemic metabolic syndrome. As of today, there is no broadly accepted method for the diagnosis of hepatic steatosis in contrast-enhanced CT images. This retrospective study evaluates the potential of quantitative iodine values in portal venous phase iodine images in dual-energy CT (DECT) by measuring iodine concentrations in regions of interest (ROI) and analyzing the absolute iodine concentration of the liver parenchyma as well as three different blood-normalized iodine concentrations in a study cohort of 251 patients. An independent two sample t-test (p < 0.05) was used to compare the iodine concentrations of healthy and fatty liver. Diagnostic performance was assessed by ROC (receiver operating characteristic) curve analysis. The results showed significant differences between the average iodine concentration of healthy and fatty liver parenchyma for the absolute and for the blood-normalized iodine concentrations. The study concludes that the iodine uptake of the liver parenchyma is impaired by hepatic steatosis, and that the measurement of iodine concentration can provide a suitable method for the detection of hepatic steatosis in quantitative iodine images. Suitable thresholds of quantitative iodine concentration values for the diagnosis of hepatic steatosis are provided.
Keyphrases
- dual energy
- computed tomography
- contrast enhanced
- image quality
- magnetic resonance imaging
- metabolic syndrome
- deep learning
- high resolution
- magnetic resonance
- positron emission tomography
- optical coherence tomography
- type diabetes
- newly diagnosed
- chronic kidney disease
- cardiovascular disease
- end stage renal disease
- insulin resistance
- prognostic factors
- skeletal muscle
- quantum dots
- diffusion weighted imaging
- fatty acid
- data analysis