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CT三维容积分析在实性肺结节恶性风险度评估中的价值

BACKGROUND AND OBJECTIVE: The management of pulmonary nodules relies on cancer risk assessment, in which the only widely accepted criterion is diameter. The development of volumetric computed tomography (CT) and three-dimensional (3D) software enhances the clarity in displaying the nodules' cha...

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Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5973050/
https://www.ncbi.nlm.nih.gov/pubmed/27215456
http://dx.doi.org/10.3779/j.issn.1009-3419.2016.05.05
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collection PubMed
description BACKGROUND AND OBJECTIVE: The management of pulmonary nodules relies on cancer risk assessment, in which the only widely accepted criterion is diameter. The development of volumetric computed tomography (CT) and three-dimensional (3D) software enhances the clarity in displaying the nodules' characteristics. This study evaluated the values of the nodules' volume and 3D morphological characteristics (edge, shape and location) in cancer risk assessment. METHODS: The CT data of 200 pulmonary nodules were retrospectively evaluated using 3D volumetric software. The malignancy or benignity of all the nodules was confirmed by pathology, histology or follow up (>2 years). Logistic regression analysis was performed to calculate the odds ratios (ORs) of the 3D margin (smooth, lobulated or spiculated/irregular), shape (spherical or non-spherical), location (purely intraparenchymal, juxtavascular or pleural-attached), and nodule volume in cancer risk assessment for total and sub-centimeter nodules. The receiver operating characteristic (ROC) curve was employed to determine the optimal threshold for the nodule volume. RESULTS: Out of 200 pulmonary nodules, 78 were malignant, whereas 122 were benign. The Logistic regression analysis showed that the volume (OR=3.3; P < 0.001) and the 3D margin (OR=13.4, 9.8; both P=0.001) were independent predictive factors of malignancy, whereas the location and 3D shape exhibited no total predictive value (P>0.05). ROC analysis showed that the optimal threshold for malignancy was 666 mm(3). For sub-centimeter nodules, the 3D margin was the only valuable predictive factor of malignancy (OR=60.5, 75.0; P=0.003, 0.007). CONCLUSION: The volume and 3D margin are important factors considered to assess the cancer risk of pulmonary nodules. Volumes larger than 666 mm(3) can be determined as high risk for pulmonary nodules; by contrast, nodules with lobulated, spiculated, or irregular margin present a high malignancy probability.
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spelling pubmed-59730502018-07-06 CT三维容积分析在实性肺结节恶性风险度评估中的价值 Zhongguo Fei Ai Za Zhi 临床研究 BACKGROUND AND OBJECTIVE: The management of pulmonary nodules relies on cancer risk assessment, in which the only widely accepted criterion is diameter. The development of volumetric computed tomography (CT) and three-dimensional (3D) software enhances the clarity in displaying the nodules' characteristics. This study evaluated the values of the nodules' volume and 3D morphological characteristics (edge, shape and location) in cancer risk assessment. METHODS: The CT data of 200 pulmonary nodules were retrospectively evaluated using 3D volumetric software. The malignancy or benignity of all the nodules was confirmed by pathology, histology or follow up (>2 years). Logistic regression analysis was performed to calculate the odds ratios (ORs) of the 3D margin (smooth, lobulated or spiculated/irregular), shape (spherical or non-spherical), location (purely intraparenchymal, juxtavascular or pleural-attached), and nodule volume in cancer risk assessment for total and sub-centimeter nodules. The receiver operating characteristic (ROC) curve was employed to determine the optimal threshold for the nodule volume. RESULTS: Out of 200 pulmonary nodules, 78 were malignant, whereas 122 were benign. The Logistic regression analysis showed that the volume (OR=3.3; P < 0.001) and the 3D margin (OR=13.4, 9.8; both P=0.001) were independent predictive factors of malignancy, whereas the location and 3D shape exhibited no total predictive value (P>0.05). ROC analysis showed that the optimal threshold for malignancy was 666 mm(3). For sub-centimeter nodules, the 3D margin was the only valuable predictive factor of malignancy (OR=60.5, 75.0; P=0.003, 0.007). CONCLUSION: The volume and 3D margin are important factors considered to assess the cancer risk of pulmonary nodules. Volumes larger than 666 mm(3) can be determined as high risk for pulmonary nodules; by contrast, nodules with lobulated, spiculated, or irregular margin present a high malignancy probability. 中国肺癌杂志编辑部 2016-05-20 /pmc/articles/PMC5973050/ /pubmed/27215456 http://dx.doi.org/10.3779/j.issn.1009-3419.2016.05.05 Text en 版权所有©《中国肺癌杂志》编辑部2016 https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/
spellingShingle 临床研究
CT三维容积分析在实性肺结节恶性风险度评估中的价值
title CT三维容积分析在实性肺结节恶性风险度评估中的价值
title_full CT三维容积分析在实性肺结节恶性风险度评估中的价值
title_fullStr CT三维容积分析在实性肺结节恶性风险度评估中的价值
title_full_unstemmed CT三维容积分析在实性肺结节恶性风险度评估中的价值
title_short CT三维容积分析在实性肺结节恶性风险度评估中的价值
title_sort ct三维容积分析在实性肺结节恶性风险度评估中的价值
topic 临床研究
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5973050/
https://www.ncbi.nlm.nih.gov/pubmed/27215456
http://dx.doi.org/10.3779/j.issn.1009-3419.2016.05.05
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