Tissue-equivalent materials are used for simplifying quality control and quality assurance procedures, both in diagnostic and therapeutic radiology. Important information to formulate a tissue-equivalent material is elemental composition of its base materials. However, this information is not easily obtained. Therefore we propose a stoichiometric analysis method to investigate the elemental composition of the base materials that can potentially be used for manufacturing tissue-equivalent materials. In this technique, we combined the stoichiometric calibration and the basic data method to obtain the elemental composition of materials from measured computer tomography (CT) numbers. The elemental composition, with the maximum number of the elements of the material in question up to the available number of different tube voltages at the CT scanner, was analysed using the proposed approach. We tested eight different cylinders in this study. The estimated elemental compositions of unspecified materials in the cylinders were evaluated by comparing the calculated and the simulated CT numbers to the measured ones; the results showed good correlation with maximum absolute differences of 1.9 and 3.7 HU, respectively. The accuracy of the stoichiometric analysis method to estimate the elemental composition was influenced by the accuracy of the measured CT numbers. The method proposed allows for determining the elemental composition of the base materials which can then be applied further to formulate tissue-equivalent materials.

Download full-text PDF

Source
http://dx.doi.org/10.1088/0031-9155/56/10/005DOI Listing

Publication Analysis

Top Keywords

elemental composition
28
tissue-equivalent materials
16
formulate tissue-equivalent
12
composition base
12
base materials
12
materials
9
elemental
8
stoichiometric analysis
8
analysis method
8
composition
7

Similar Publications

Quantifying changes in the properties of smoke aerosols under varying conditions is important for understanding the health and environmental impacts of exposure to smoke. Smoke composition, aerosol liquid water content, effective density (ρ), and other properties can change significantly as smoke travels through areas under different ambient conditions and over time. During this study, we measured changes in smoke composition and physical properties due to oxidative aging and exposure to humidity.

View Article and Find Full Text PDF

Loading with non-metal cocatalysts to regulate interfacial charge transfer and separation has become a prominent focus in current research. In this study, g-CN/CNT composites loaded with non-metallic cocatalysts were prepared through pyrolysis using urea and CNTs. Various characterization techniques, including transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ultraviolet-visible diffuse reflectance spectroscopy (UV-vis DRS), photoelectrochemical (PEC) analysis, fluorescence lifetime spectroscopy (TRPL), electron paramagnetic resonance spectroscopy (ESR), and photoluminescence (PL) spectroscopy, were employed to analyze the sample's microstructure, phase composition, elemental chemical states, and photoelectronic properties.

View Article and Find Full Text PDF

Light-driven in-situ synthesis of nano-sulfur and graphene oxide composites for efficient removal of heavy metal ions.

J Hazard Mater

January 2025

State Key Lab of Geohazard prevention & Geoenvironment protection, College of Materials and Chemistry & Chemical Engineering, Chengdu University of Technology, Chengdu 610059, China. Electronic address:

Sulfur nanoparticles (SNPs) and their composites are promising for heavy metal adsorption, yet current SNPs often lack surface S, leading to low affinity toward heavy metal and ease of aggregation. Here, we report a simple light-driven method for facile prepare SNPs with surfaces enriched with S and in-situ load them onto graphene oxide (GO) to fabricate GO-S composites. Under illumination, the O generated by photosensitizer phloxine B was able to oxidize S into elemental SNPs.

View Article and Find Full Text PDF

Accurate dose predictions are crucial to maximizing the benefits of carbon-ion therapy. Carbon beams incident on the human body cause nuclear interactions with tissues, resulting in changes in the constituent nuclides and leading to dose errors that are conventionally corrected using conventional single-energy computed tomography (SECT). Dual-energy computed tomography (DECT) has frequently been used for stopping power estimation in particle therapy and is well suited for correcting nuclear reactions because of its detailed body-tissue elemental information.

View Article and Find Full Text PDF

This study introduces a hybrid network model for phase classification, integrating quantum networks and complex-valued neural networks. This architecture uses elemental composition as its only input, eliminating complex feature engineering. Parameterized quantum networks handle sparse elemental data and convert data from real to complex domains, increasing information dimensionality.

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!