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Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation

BACKGROUND: Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation...

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Autores principales: Fukugawa, Yoshiyuki, Toya, Ryo, Matsuyama, Tomohiko, Watakabe, Takahiro, Shimohigashi, Yoshinobu, Kai, Yudai, Matsumoto, Tadashi, Oya, Natsuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450459/
https://www.ncbi.nlm.nih.gov/pubmed/36068498
http://dx.doi.org/10.1186/s12880-022-00889-0
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author Fukugawa, Yoshiyuki
Toya, Ryo
Matsuyama, Tomohiko
Watakabe, Takahiro
Shimohigashi, Yoshinobu
Kai, Yudai
Matsumoto, Tadashi
Oya, Natsuo
author_facet Fukugawa, Yoshiyuki
Toya, Ryo
Matsuyama, Tomohiko
Watakabe, Takahiro
Shimohigashi, Yoshinobu
Kai, Yudai
Matsumoto, Tadashi
Oya, Natsuo
author_sort Fukugawa, Yoshiyuki
collection PubMed
description BACKGROUND: Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation in delineating gross tumor volume (GTV) of TC. METHODS: Eighteen patients with TC with dental fillings were enrolled in this study. Contrast-enhanced CT simulator images were reconstructed using the conventional (CT(CONV)) and MAR algorithm (CT(MAR)). Four board-certified radiation oncologists delineated the GTV of primary tumors using routine clinical data first on CT(CONV) image datasets (GTV(CONV)), followed by CT(CONV) and CT(MAR) fused image datasets (GTV(MAR)) at least 2 weeks apart. Intermodality differences in GTV values and Dice similarity coefficient (DSC) were compared using Wilcoxon’s signed-rank test. RESULTS: GTV(MAR) was significantly smaller than GTV(CONV) for three observers. The other observer showed no significant difference between GTV(CONV) and GTV(MAR) values. For all four observers, the mean GTV(CONV) and GTV(MAR) values were 14.0 (standard deviation [SD]: 7.4) cm(3) and 12.1 (SD: 6.4) cm(3), respectively, with the latter significantly lower than the former (p < 0.001). The mean DSC of GTV(CONV) and GTV(MAR) was 0.74 (SD: 0.10) and 0.77 (SD: 0.10), respectively, with the latter significantly higher than that of the former (p < 0.001). CONCLUSIONS: The use of the MAR algorithm led to the delineation of smaller GTVs and reduced interobserver variations in delineating GTV of the primary tumors in patients with TC.
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spelling pubmed-94504592022-09-08 Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation Fukugawa, Yoshiyuki Toya, Ryo Matsuyama, Tomohiko Watakabe, Takahiro Shimohigashi, Yoshinobu Kai, Yudai Matsumoto, Tadashi Oya, Natsuo BMC Med Imaging Research BACKGROUND: Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation in delineating gross tumor volume (GTV) of TC. METHODS: Eighteen patients with TC with dental fillings were enrolled in this study. Contrast-enhanced CT simulator images were reconstructed using the conventional (CT(CONV)) and MAR algorithm (CT(MAR)). Four board-certified radiation oncologists delineated the GTV of primary tumors using routine clinical data first on CT(CONV) image datasets (GTV(CONV)), followed by CT(CONV) and CT(MAR) fused image datasets (GTV(MAR)) at least 2 weeks apart. Intermodality differences in GTV values and Dice similarity coefficient (DSC) were compared using Wilcoxon’s signed-rank test. RESULTS: GTV(MAR) was significantly smaller than GTV(CONV) for three observers. The other observer showed no significant difference between GTV(CONV) and GTV(MAR) values. For all four observers, the mean GTV(CONV) and GTV(MAR) values were 14.0 (standard deviation [SD]: 7.4) cm(3) and 12.1 (SD: 6.4) cm(3), respectively, with the latter significantly lower than the former (p < 0.001). The mean DSC of GTV(CONV) and GTV(MAR) was 0.74 (SD: 0.10) and 0.77 (SD: 0.10), respectively, with the latter significantly higher than that of the former (p < 0.001). CONCLUSIONS: The use of the MAR algorithm led to the delineation of smaller GTVs and reduced interobserver variations in delineating GTV of the primary tumors in patients with TC. BioMed Central 2022-09-06 /pmc/articles/PMC9450459/ /pubmed/36068498 http://dx.doi.org/10.1186/s12880-022-00889-0 Text en © The Author(s) 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Fukugawa, Yoshiyuki
Toya, Ryo
Matsuyama, Tomohiko
Watakabe, Takahiro
Shimohigashi, Yoshinobu
Kai, Yudai
Matsumoto, Tadashi
Oya, Natsuo
Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title_full Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title_fullStr Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title_full_unstemmed Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title_short Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
title_sort impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450459/
https://www.ncbi.nlm.nih.gov/pubmed/36068498
http://dx.doi.org/10.1186/s12880-022-00889-0
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