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Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis
BACKGROUND: Dual-energy computed tomography has shown a great interest for musculoskeletal pathologies. Photon-counting spectral computed tomography (PCSCT) can acquire data in multiple energy bins with the potential to increase contrast, especially for soft tissues. Our objectives were to assess th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8861235/ https://www.ncbi.nlm.nih.gov/pubmed/35190914 http://dx.doi.org/10.1186/s41747-021-00261-x |
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author | Chappard, Christine Abascal, Juan Olivier, Cécile Si-Mohamed, Salim Boussel, Loic Piala, Jean Baptiste Douek, Philippe Peyrin, Francoise |
author_facet | Chappard, Christine Abascal, Juan Olivier, Cécile Si-Mohamed, Salim Boussel, Loic Piala, Jean Baptiste Douek, Philippe Peyrin, Francoise |
author_sort | Chappard, Christine |
collection | PubMed |
description | BACKGROUND: Dual-energy computed tomography has shown a great interest for musculoskeletal pathologies. Photon-counting spectral computed tomography (PCSCT) can acquire data in multiple energy bins with the potential to increase contrast, especially for soft tissues. Our objectives were to assess the value of PCSST to characterise cartilage and to extract quantitative measures of subchondral bone integrity. METHODS: Seven excised human knees (3 males and 4 females; 4 normal and 3 with osteoarthritis; age 80.6 ± 14 years, mean ± standard deviation) were scanned using a clinical PCSCT prototype scanner. Tomographic image reconstruction was performed after Compton/photoelectric decomposition. Virtual monoenergetic images were generated from 40 keV to 110 keV every 10 keV (cubic voxel size 250 × 250 × 250 μm(3)). After selecting an optimal virtual monoenergetic image, we analysed the grey level histograms of different tissues and extracted quantitative measurements on bone cysts. RESULTS: The optimal monoenergetic images were obtained for 60 keV and 70 keV. Visual inspection revealed that these images provide sufficient spatial resolution and soft-tissue contrast to characterise surfaces, disruption, calcification of cartilage, bone osteophytes, and bone cysts. Analysis of attenuation versus energy revealed different energy fingerprint according to tissues. The volumes and numbers of bone cyst were quantified. CONCLUSIONS: Virtual monoenergetic images may provide direct visualisation of both cartilage and bone details. Thus, unenhanced PCSCT appears to be a new modality for characterising the knee joint with the potential to increase the diagnostic capability of computed tomography for joint diseases and osteoarthritis. |
format | Online Article Text |
id | pubmed-8861235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-88612352022-03-02 Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis Chappard, Christine Abascal, Juan Olivier, Cécile Si-Mohamed, Salim Boussel, Loic Piala, Jean Baptiste Douek, Philippe Peyrin, Francoise Eur Radiol Exp Original Article BACKGROUND: Dual-energy computed tomography has shown a great interest for musculoskeletal pathologies. Photon-counting spectral computed tomography (PCSCT) can acquire data in multiple energy bins with the potential to increase contrast, especially for soft tissues. Our objectives were to assess the value of PCSST to characterise cartilage and to extract quantitative measures of subchondral bone integrity. METHODS: Seven excised human knees (3 males and 4 females; 4 normal and 3 with osteoarthritis; age 80.6 ± 14 years, mean ± standard deviation) were scanned using a clinical PCSCT prototype scanner. Tomographic image reconstruction was performed after Compton/photoelectric decomposition. Virtual monoenergetic images were generated from 40 keV to 110 keV every 10 keV (cubic voxel size 250 × 250 × 250 μm(3)). After selecting an optimal virtual monoenergetic image, we analysed the grey level histograms of different tissues and extracted quantitative measurements on bone cysts. RESULTS: The optimal monoenergetic images were obtained for 60 keV and 70 keV. Visual inspection revealed that these images provide sufficient spatial resolution and soft-tissue contrast to characterise surfaces, disruption, calcification of cartilage, bone osteophytes, and bone cysts. Analysis of attenuation versus energy revealed different energy fingerprint according to tissues. The volumes and numbers of bone cyst were quantified. CONCLUSIONS: Virtual monoenergetic images may provide direct visualisation of both cartilage and bone details. Thus, unenhanced PCSCT appears to be a new modality for characterising the knee joint with the potential to increase the diagnostic capability of computed tomography for joint diseases and osteoarthritis. Springer International Publishing 2022-02-22 /pmc/articles/PMC8861235/ /pubmed/35190914 http://dx.doi.org/10.1186/s41747-021-00261-x Text en © The Author(s) under exclusive licence to European Society of Radiology 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Chappard, Christine Abascal, Juan Olivier, Cécile Si-Mohamed, Salim Boussel, Loic Piala, Jean Baptiste Douek, Philippe Peyrin, Francoise Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title | Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title_full | Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title_fullStr | Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title_full_unstemmed | Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title_short | Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
title_sort | virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8861235/ https://www.ncbi.nlm.nih.gov/pubmed/35190914 http://dx.doi.org/10.1186/s41747-021-00261-x |
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