Algorithm for using dual energy computed tomography to determine chemical composition: A feasibility study

Using dual-energy computed tomography (CT), this study aims to develop an algorithm to identify the chemical constituents of an unknown material (compound or mixture) and improve the accuracy of material discrimination. The algorithm requires mass attenuation coefficients (MAC) that were obtained using a dual energy CT as an input, identifies the elemental composition, and then calculates its weight fraction. To evaluate the functionality of the developed algorithm, it was used to determine the chemical constituents for human tissues. Furthermore, the results were compared with those provided by the National Institute of Standards and Technology (NIST). We used dual energies 80/140 kVp for spectral CT scans, as inputs to the algorithm, in addition to a set of 50/80 and 80/100 keV for mono-energetic X-rays. The algorithm correctly determined the chemical constituent elements of unknown materials. Results were obtained for the fractional weights of each component for mono-energetic X-rays and spectral X-ray use. For mono-energetic X-rays, the differences were < 0.01% for compounds and 6.02% for mixture, respectively. For the spectral X-rays, the differences in 2.98% for compounds and 6.03% for mixtures, respectively. We developed an algorithm to determine the type and weight fraction of an element using the MAC of dual-energy CT. The algorithm can exclude the inherent uncertainty of SPR calculations and improve the accuracy of dose calculations in radiation therapy planning.

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Publication Details

Journal
PLoS ONE
Published
2025-06-30
DOI
https://doi.org/10.1371/journal.pone.0322805
Primary Topic
Advanced X-ray and CT Imaging
Type
article
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article

Algorithm for using dual energy computed tomography to determine chemical composition: A feasibility study

Dong Hyeok Choi, Min Cheol Han, Kwangwoo Park, Jin Sung Kim et al.
PLoS ONE
Advanced X-ray and CT Imaging
article

Algorithm for using dual energy computed tomography to determine chemical composition: A feasibility study

Dong Hyeok Choi, Min Cheol Han, Kwangwoo Park, Jin Sung Kim, So Hyun Ahn
article en

Abstract

Using dual-energy computed tomography (CT), this study aims to develop an algorithm to identify the chemical constituents of an unknown material (compound or mixture) and improve the accuracy of material discrimination. The algorithm requires mass attenuation coefficients (MAC) that were obtained using a dual energy CT as an input, identifies the elemental composition, and then calculates its weight fraction. To evaluate the functionality of the developed algorithm, it was used to determine the chemical constituents for human tissues. Furthermore, the results were compared with those provided by the National Institute of Standards and Technology (NIST). We used dual energies 80/140 kVp for spectral CT scans, as inputs to the algorithm, in addition to a set of 50/80 and 80/100 keV for mono-energetic X-rays. The algorithm correctly determined the chemical constituent elements of unknown materials. Results were obtained for the fractional weights of each component for mono-energetic X-rays and spectral X-ray use. For mono-energetic X-rays, the differences were < 0.01% for compounds and 6.02% for mixture, respectively. For the spectral X-rays, the differences in 2.98% for compounds and 6.03% for mixtures, respectively. We developed an algorithm to determine the type and weight fraction of an element using the MAC of dual-energy CT. The algorithm can exclude the inherent uncertainty of SPR calculations and improve the accuracy of dose calculations in radiation therapy planning.

PLoS ONEVol. 20(6)
Ewha Womans University (KR), Yonsei University (KR), Severance Hospital (KR), Ewha Womans University Medical Center (KR)
Peace, Justice and strong institutions
Openalex Percentile: Top 86%
Advanced X-ray and CT Imaging
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Algorithm for using dual energy computed tomography to determine chemical composition: A feasibility study — Dong Hyeok Choi, Min Cheol Han, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS