Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications

Abstract In this study, preclinical experiments were performed with an in-house developed prototypal photon-counting detector computed tomography (PCD CT) system. The performance of the system was compared with the conventional energy-integrating detector (EID)-based CT, concerning the basic image q...

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Autores principales:	Chang-Lae Lee, Key Jo Hong, Namwoo Kim, Kwanhee Han, Dongkyu Kim, Hoe-Su Jung, Sangmin Lee, Junyoung Park, Kyoung-Yong Lee, Jee Eun Lee, Yuna Choi, Minkook Cho
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/36af6de9e3c843e89f0e40840098db49
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spelling	oai:doaj.org-article:36af6de9e3c843e89f0e40840098db492021-11-28T12:15:42ZFeasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications10.1038/s41598-021-02210-52045-2322https://doaj.org/article/36af6de9e3c843e89f0e40840098db492021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02210-5https://doaj.org/toc/2045-2322Abstract In this study, preclinical experiments were performed with an in-house developed prototypal photon-counting detector computed tomography (PCD CT) system. The performance of the system was compared with the conventional energy-integrating detector (EID)-based CT, concerning the basic image quality biomarkers and the respective capacities for material separation. The pre- and the post-contrast axial images of a canine brain captured by the PCD CT and EID CT systems were found to be visually similar. Multi-energy images were acquired using the PCD CT system, and machine learning-based material decomposition was performed to segment the white and gray matters for the first time in soft tissue segmentation. Furthermore, to accommodate clinical applications that require high resolution acquisitions, a small, native, high-resolution (HR) detector was implemented on the PCD CT system, and its performance was evaluated based on animal experiments. The HR acquisition mode improved the spatial resolution and delineation of the fine structures in the canine’s nasal turbinates compared to the standard mode. Clinical applications that rely on high-spatial resolution expectedly will also benefit from this resolution-enhancing function. The results demonstrate the potential impact on the brain tissue segmentation, improved detection of the liver tumors, and capacity to reconstruct high-resolution images both preclinically and clinically.Chang-Lae LeeKey Jo HongNamwoo KimKwanhee HanDongkyu KimHoe-Su JungSangmin LeeJunyoung ParkKyoung-Yong LeeJee Eun LeeYuna ChoiMinkook ChoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chang-Lae Lee Key Jo Hong Namwoo Kim Kwanhee Han Dongkyu Kim Hoe-Su Jung Sangmin Lee Junyoung Park Kyoung-Yong Lee Jee Eun Lee Yuna Choi Minkook Cho Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
description	Abstract In this study, preclinical experiments were performed with an in-house developed prototypal photon-counting detector computed tomography (PCD CT) system. The performance of the system was compared with the conventional energy-integrating detector (EID)-based CT, concerning the basic image quality biomarkers and the respective capacities for material separation. The pre- and the post-contrast axial images of a canine brain captured by the PCD CT and EID CT systems were found to be visually similar. Multi-energy images were acquired using the PCD CT system, and machine learning-based material decomposition was performed to segment the white and gray matters for the first time in soft tissue segmentation. Furthermore, to accommodate clinical applications that require high resolution acquisitions, a small, native, high-resolution (HR) detector was implemented on the PCD CT system, and its performance was evaluated based on animal experiments. The HR acquisition mode improved the spatial resolution and delineation of the fine structures in the canine’s nasal turbinates compared to the standard mode. Clinical applications that rely on high-spatial resolution expectedly will also benefit from this resolution-enhancing function. The results demonstrate the potential impact on the brain tissue segmentation, improved detection of the liver tumors, and capacity to reconstruct high-resolution images both preclinically and clinically.
format	article
author	Chang-Lae Lee Key Jo Hong Namwoo Kim Kwanhee Han Dongkyu Kim Hoe-Su Jung Sangmin Lee Junyoung Park Kyoung-Yong Lee Jee Eun Lee Yuna Choi Minkook Cho
author_facet	Chang-Lae Lee Key Jo Hong Namwoo Kim Kwanhee Han Dongkyu Kim Hoe-Su Jung Sangmin Lee Junyoung Park Kyoung-Yong Lee Jee Eun Lee Yuna Choi Minkook Cho
author_sort	Chang-Lae Lee
title	Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
title_short	Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
title_full	Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
title_fullStr	Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
title_full_unstemmed	Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
title_sort	feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/36af6de9e3c843e89f0e40840098db49
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_version_	1718408070621560832

Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications

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