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Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions

RESULTS: The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P = 0.480–0.670). However, significant differences in the texture features of monochromatic images...

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Autores principales: Tomita, Hayato, Kuno, Hirofumi, Sekiya, Kotaro, Otani, Katharina, Sakai, Osamu, Li, Baojun, Hiyama, Takashi, Nomura, Keiichi, Mimura, Hidefumi, Kobayashi, Tatsushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7104273/
https://www.ncbi.nlm.nih.gov/pubmed/32256574
http://dx.doi.org/10.1155/2020/5484671
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author Tomita, Hayato
Kuno, Hirofumi
Sekiya, Kotaro
Otani, Katharina
Sakai, Osamu
Li, Baojun
Hiyama, Takashi
Nomura, Keiichi
Mimura, Hidefumi
Kobayashi, Tatsushi
author_facet Tomita, Hayato
Kuno, Hirofumi
Sekiya, Kotaro
Otani, Katharina
Sakai, Osamu
Li, Baojun
Hiyama, Takashi
Nomura, Keiichi
Mimura, Hidefumi
Kobayashi, Tatsushi
author_sort Tomita, Hayato
collection PubMed
description RESULTS: The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P = 0.480–0.670). However, significant differences in the texture features of monochromatic images were observed between benign and malignant nodules: histogram mean and median, co-occurrence matrix contrast, gray-level gradient matrix (GLGM) skewness, and mean gradients and variance of gradients for GLGM at 80 keV (P = 0.014–0.044). The highest AUC was 0.77, for the histogram mean and median of images acquired at 80 keV. CONCLUSIONS: Texture features extracted from monochromatic images using DECT, specifically acquired at high keV, may be a promising diagnostic approach for thyroid nodules. A further large study for incidental thyroid nodules using DECT texture analysis is required to validate our results.
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spelling pubmed-71042732020-04-03 Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions Tomita, Hayato Kuno, Hirofumi Sekiya, Kotaro Otani, Katharina Sakai, Osamu Li, Baojun Hiyama, Takashi Nomura, Keiichi Mimura, Hidefumi Kobayashi, Tatsushi Int J Endocrinol Research Article RESULTS: The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P = 0.480–0.670). However, significant differences in the texture features of monochromatic images were observed between benign and malignant nodules: histogram mean and median, co-occurrence matrix contrast, gray-level gradient matrix (GLGM) skewness, and mean gradients and variance of gradients for GLGM at 80 keV (P = 0.014–0.044). The highest AUC was 0.77, for the histogram mean and median of images acquired at 80 keV. CONCLUSIONS: Texture features extracted from monochromatic images using DECT, specifically acquired at high keV, may be a promising diagnostic approach for thyroid nodules. A further large study for incidental thyroid nodules using DECT texture analysis is required to validate our results. Hindawi 2020-03-18 /pmc/articles/PMC7104273/ /pubmed/32256574 http://dx.doi.org/10.1155/2020/5484671 Text en Copyright © 2020 Hayato Tomita et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tomita, Hayato
Kuno, Hirofumi
Sekiya, Kotaro
Otani, Katharina
Sakai, Osamu
Li, Baojun
Hiyama, Takashi
Nomura, Keiichi
Mimura, Hidefumi
Kobayashi, Tatsushi
Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title_full Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title_fullStr Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title_full_unstemmed Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title_short Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions
title_sort quantitative assessment of thyroid nodules using dual-energy computed tomography: iodine concentration measurement and multiparametric texture analysis for differentiating between malignant and benign lesions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7104273/
https://www.ncbi.nlm.nih.gov/pubmed/32256574
http://dx.doi.org/10.1155/2020/5484671
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