Rationale And Objectives: The purpose of this study was to investigate the potential effects of patient size and radiation dose on the accuracy of iodine quantification using dual-source dual-energy computed tomography (CT).

Materials And Methods: Three phantoms representing different patient sizes were constructed, containing iodine inserts with concentrations from 0 to 20 mg/ml. Dual-energy CT scans were performed at six dose levels from 2 to 30 mGy. Iodine concentrations were measured using a three-material-decomposition algorithm and their accuracy was assessed.

Results: In a small phantom, iodine quantification was accurate and consistent at all dose levels. In a medium phantom, minor underestimations were observed, and the results were consistent except at low dose. In the large phantom, more significant underestimation of iodine concentration was observed at higher doses (≥15 mGy), which was attributed to the beam-hardening effect. At lower doses, increasing upward bias was observed in the CT number, leading to significant overestimations of both iodine concentration and fat fraction, which was attributed to the photon-starvation effect. The severity of the latter effect was determined by mA instead of mAs, suggesting that the electronic noise, rather than the quantum noise, was responsible for the bias. Using higher kVp for the low-energy tube was found to alleviate these effects.

Conclusion: Reliable iodine quantification can be achieved using dual-source CT, but the result can be affected by patient size and dose rate. In large patients, biases may occur due to the beam-hardening and the photon-starvation effects, in which case higher dose rate and higher kVp are recommended to minimize these effects.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.acra.2019.12.027DOI Listing

Publication Analysis

Top Keywords

iodine quantification
16
patient size
12
effects patient
8
size radiation
8
radiation dose
8
iodine
8
quantification dual-source
8
dual-source dual-energy
8
dose levels
8
iodine concentration
8

Similar Publications

: The number of incidental renal lesions identified in CT scans of the abdomen is increasing. Objective: The aim of this study was to determine whether hyperdense renal lesions without solid components in a portal venous CT scan can be clearly classified as vascular or non-vascular by material decomposition into iodine and water. This retrospective single-center study included 26 patients (mean age 72 years ± 9; 16 male) with 42 hyperdense renal lesions (>20 HU) in a contrast-enhanced Photon-Counting Detector CT scan (PCD-CT) between May and December 2022.

View Article and Find Full Text PDF

To exclusively evaluate, in vitro, the efficacy of five intracanal medicaments against Candida albicans and Enterococcus faecalis in infected single-rooted primary teeth. Forty-three teeth were selected, out of which 42 were simultaneously contaminated with C. albicans and E.

View Article and Find Full Text PDF

Spatial and temporal evaluation of iodine uptake and radiodensity in meniscus tissue using contrast-enhanced micro-CT.

Heliyon

December 2024

Empa - Swiss Federal Laboratories for Materials Science and Technology, 8600, Dübendorf, Switzerland.

Rationale And Objective: The visualization of soft tissues, like the meniscus, through X-ray micro-computed tomography (micro-CT), requires the use of contrast agents (CAs). While other studies have investigated CA diffusion in fibrocartilagineous tissues, this work aimed to optimize iodine staining protocols for meniscal tissue that improve their visualization by micro-CT. Specific objectives included evaluating the diffusion of CAs within meniscal samples over time, assessing volume changes due to staining, and identifying the iodine ions absorbed by the tissue.

View Article and Find Full Text PDF

The determination of iodine after the enrichment on solid sorbent ZrO in the combination with molecular absorption spectrometric (MAS) detection is presented. The detection limit and enrichment factor obtained were 0.009 μg mL and 9, respectively.

View Article and Find Full Text PDF

Enhanced iodinated disinfection byproducts formation in iodide/iodate-containing water undergoing UV-chloramine sequential disinfection: Machine learning-aided identification of reaction mechanisms.

Water Res

December 2024

State Key Laboratory of Pollution Control and Resource Reuse, Key Laboratory of Urban Water Supply, Water Saving and Water Environment Governance in the Yangtze River Delta of Ministry of Water Resources, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, PR China. Electronic address:

Restricted to the complex nature of dissolved organic matter (DOM) in various aquatic environments, the mechanisms of enhanced iodinated disinfection byproducts (I-DBPs) formation in water containing both I and IO (designated as I/IO in this study) during the ultraviolet (UV)-chloramine sequential disinfection process remains unclear. In this study, four machine learning (ML) models were established to predict I-DBP formation by using DOM and disinfection features as input variables. Extreme gradient boosting (XGB) algorithm outperformed the others in model development using synthetic waters and in cross-dataset generalization of surface waters.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!