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Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer
This study aimed to compare the quality of virtual low-keV monoenergetic images vs conventional images reconstructed from dual-layer spectral detector computed tomography (SDCT) for the detection of peritoneal implants of ovarian cancer. Fifty ovarian cancer patients who underwent abdominopelvic SDC...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306341/ https://www.ncbi.nlm.nih.gov/pubmed/32501991 http://dx.doi.org/10.1097/MD.0000000000020444 |
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author | Kim, Taek Min Kim, Sang Youn Cho, Jeong Yeon Kim, Seung Hyup Moon, Min Hoan |
author_facet | Kim, Taek Min Kim, Sang Youn Cho, Jeong Yeon Kim, Seung Hyup Moon, Min Hoan |
author_sort | Kim, Taek Min |
collection | PubMed |
description | This study aimed to compare the quality of virtual low-keV monoenergetic images vs conventional images reconstructed from dual-layer spectral detector computed tomography (SDCT) for the detection of peritoneal implants of ovarian cancer. Fifty ovarian cancer patients who underwent abdominopelvic SDCT scans were included in this retrospective study. Virtual monoenergetic images at 40 (VMI(40)) and 50 keV (VMI(50)), and two conventional images were reconstructed using filtered back projection (FBP) and iterative model reconstruction (IMR) protocols. The mean attenuation of the peritoneal implant, signal-to-noise ratio (SNR), contrast-to-noise ratio relative to ascites (CNR(A)) and adjacent reference tissues (e.g., bowel wall, hepatic, or splenic parenchyma [CNR(B)]) were calculated and compared using paired t tests. Qualitative image analysis regarding overall image quality, image noise, image blurring, lesion conspicuity, was performed by two radiologists. A subgroup analysis according to the peritoneal implant region was also conducted. VMI(40) yielded significantly higher mean attenuation (183.35) of SNR and CNR values (SNR 11.69, CNR(A) 7.39, CNR(B) 2.68), compared to VMI(50), IR, and FBP images (P < .001). The mean attenuation (129.65), SNR and CNR values (SNR 9.37, CNR(A) 5.72, CNR(B) 2.02) of VMI(50) were also significantly higher than those of IR and FBP images (P < .001). In the subgroup analysis, all values were significantly higher on VMI(40) regardless of the peritoneal implant region (P < .05). In both readers, overall image quality and image blurring showed highest score in VMI(50), while image noise and lesion conspicuity showed best score in IMR and VMI(40) respectively. Inter-reader agreements are moderate to almost perfect in every parameter. The low-keV VMIs improved both quantitative assessment and lesion conspicuity of peritoneal implants from ovarian cancer compared to conventional images. |
format | Online Article Text |
id | pubmed-7306341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-73063412020-07-08 Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer Kim, Taek Min Kim, Sang Youn Cho, Jeong Yeon Kim, Seung Hyup Moon, Min Hoan Medicine (Baltimore) 6800 This study aimed to compare the quality of virtual low-keV monoenergetic images vs conventional images reconstructed from dual-layer spectral detector computed tomography (SDCT) for the detection of peritoneal implants of ovarian cancer. Fifty ovarian cancer patients who underwent abdominopelvic SDCT scans were included in this retrospective study. Virtual monoenergetic images at 40 (VMI(40)) and 50 keV (VMI(50)), and two conventional images were reconstructed using filtered back projection (FBP) and iterative model reconstruction (IMR) protocols. The mean attenuation of the peritoneal implant, signal-to-noise ratio (SNR), contrast-to-noise ratio relative to ascites (CNR(A)) and adjacent reference tissues (e.g., bowel wall, hepatic, or splenic parenchyma [CNR(B)]) were calculated and compared using paired t tests. Qualitative image analysis regarding overall image quality, image noise, image blurring, lesion conspicuity, was performed by two radiologists. A subgroup analysis according to the peritoneal implant region was also conducted. VMI(40) yielded significantly higher mean attenuation (183.35) of SNR and CNR values (SNR 11.69, CNR(A) 7.39, CNR(B) 2.68), compared to VMI(50), IR, and FBP images (P < .001). The mean attenuation (129.65), SNR and CNR values (SNR 9.37, CNR(A) 5.72, CNR(B) 2.02) of VMI(50) were also significantly higher than those of IR and FBP images (P < .001). In the subgroup analysis, all values were significantly higher on VMI(40) regardless of the peritoneal implant region (P < .05). In both readers, overall image quality and image blurring showed highest score in VMI(50), while image noise and lesion conspicuity showed best score in IMR and VMI(40) respectively. Inter-reader agreements are moderate to almost perfect in every parameter. The low-keV VMIs improved both quantitative assessment and lesion conspicuity of peritoneal implants from ovarian cancer compared to conventional images. Wolters Kluwer Health 2020-06-05 /pmc/articles/PMC7306341/ /pubmed/32501991 http://dx.doi.org/10.1097/MD.0000000000020444 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 6800 Kim, Taek Min Kim, Sang Youn Cho, Jeong Yeon Kim, Seung Hyup Moon, Min Hoan Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title | Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title_full | Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title_fullStr | Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title_full_unstemmed | Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title_short | Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
title_sort | utilization of virtual low-kev monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer |
topic | 6800 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306341/ https://www.ncbi.nlm.nih.gov/pubmed/32501991 http://dx.doi.org/10.1097/MD.0000000000020444 |
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