Solid Indeterminate Nodules with a Radiological Stability Suggesting Benignity: A Texture Analysis of Computed Tomography Images Based on the Kurtosis and Skewness of the Nodule Volume Density Histogram

Background. The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures. Objectives. T...

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Published in:Pulmonary medicine 2019, Vol.2019 (2019), p.1-7
Main Authors: Silva, Aristófanes Corrêa, Higa, Claudio, Saito, Eduardo Haruo, Lopes, Agnaldo José, Borguezan, Bruno Max, Nunes, Rodolfo Acatauassú
Format: Article
Language:English
Subjects:
Algorithms
Archives & records
Clinical medicine
CT imaging
Diagnosis, Differential
Endoscopy
Humans
Image databases
Image Processing, Computer-Assisted
Kurtosis
Lung cancer
Lung Neoplasms - diagnostic imaging
Medical imaging
Models, Statistical
Mortality
R&D
Research & development
Retrospective Studies
Sensitivity and Specificity
Skewness
Software
Solitary Pulmonary Nodule - diagnostic imaging
Specific gravity
Tomography, X-Ray Computed
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container_start_page 1
container_title Pulmonary medicine
container_volume 2019
creator Silva, Aristófanes Corrêa
Higa, Claudio
Saito, Eduardo Haruo
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Nunes, Rodolfo Acatauassú
description Background. The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures. Objectives. The present study evaluated solid indeterminate nodules with a radiological stability suggesting benignity (SINRSBs) through a texture analysis of computed tomography (CT) images. Methods. A total of 100 chest CT scans were evaluated, including 50 cases of SINRSBs and 50 cases of malignant nodules. SINRSB CT scans were performed using the same noncontrast enhanced CT protocol and equipment; the malignant nodule data were acquired from several databases. The kurtosis (KUR) and skewness (SKW) values of these tests were determined for the whole volume of each nodule, and the histograms were classified into two basic patterns: peaks or plateaus. Results. The mean (MEN) KUR values of the SINRSBs and malignant nodules were 3.37 ± 3.88 and 5.88 ± 5.11, respectively. The receiver operating characteristic (ROC) curve showed that the sensitivity and specificity for distinguishing SINRSBs from malignant nodules were 65% and 66% for KUR values >6, respectively, with an area under the curve (AUC) of 0.709 (p3.1, respectively, with an AUC of 0.709 (p
doi_str_mv 10.1155/2019/4071762
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The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures. Objectives. The present study evaluated solid indeterminate nodules with a radiological stability suggesting benignity (SINRSBs) through a texture analysis of computed tomography (CT) images. Methods. A total of 100 chest CT scans were evaluated, including 50 cases of SINRSBs and 50 cases of malignant nodules. SINRSB CT scans were performed using the same noncontrast enhanced CT protocol and equipment; the malignant nodule data were acquired from several databases. The kurtosis (KUR) and skewness (SKW) values of these tests were determined for the whole volume of each nodule, and the histograms were classified into two basic patterns: peaks or plateaus. Results. The mean (MEN) KUR values of the SINRSBs and malignant nodules were 3.37 ± 3.88 and 5.88 ± 5.11, respectively. The receiver operating characteristic (ROC) curve showed that the sensitivity and specificity for distinguishing SINRSBs from malignant nodules were 65% and 66% for KUR values &gt;6, respectively, with an area under the curve (AUC) of 0.709 (p&lt;0.0001). The MEN SKW values of the SINRSBs and malignant nodules were 1.73 ± 0.94 and 2.07 ± 1.01, respectively. The ROC curve showed that the sensitivity and specificity for distinguishing malignant nodules from SINRSBs were 65% and 66% for SKW values &gt;3.1, respectively, with an AUC of 0.709 (p&lt;0.0001). An analysis of the peak and plateau histograms revealed sensitivity, specificity, and accuracy values of 84%, 74%, and 79%, respectively. Conclusions. KUR, SKW, and histogram shape can help to noninvasively diagnose SINRSBs but should not be used alone or without considering clinical data.</description><identifier>ISSN: 2090-1836</identifier><identifier>EISSN: 2090-1844</identifier><identifier>DOI: 10.1155/2019/4071762</identifier><identifier>PMID: 31687208</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Archives &amp; records ; Clinical medicine ; CT imaging ; Diagnosis, Differential ; Endoscopy ; Humans ; Image databases ; Image Processing, Computer-Assisted ; Kurtosis ; Lung cancer ; Lung Neoplasms - diagnostic imaging ; Medical imaging ; Models, Statistical ; Mortality ; R&amp;D ; Research &amp; development ; Retrospective Studies ; Sensitivity and Specificity ; Skewness ; Software ; Solitary Pulmonary Nodule - diagnostic imaging ; Specific gravity ; Tomography, X-Ray Computed</subject><ispartof>Pulmonary medicine, 2019, Vol.2019 (2019), p.1-7</ispartof><rights>Copyright © 2019 Bruno Max Borguezan et al.</rights><rights>COPYRIGHT 2019 John Wiley &amp; Sons, Inc.</rights><rights>Copyright © 2019 Bruno Max Borguezan et al. 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The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures. Objectives. The present study evaluated solid indeterminate nodules with a radiological stability suggesting benignity (SINRSBs) through a texture analysis of computed tomography (CT) images. Methods. A total of 100 chest CT scans were evaluated, including 50 cases of SINRSBs and 50 cases of malignant nodules. SINRSB CT scans were performed using the same noncontrast enhanced CT protocol and equipment; the malignant nodule data were acquired from several databases. The kurtosis (KUR) and skewness (SKW) values of these tests were determined for the whole volume of each nodule, and the histograms were classified into two basic patterns: peaks or plateaus. Results. The mean (MEN) KUR values of the SINRSBs and malignant nodules were 3.37 ± 3.88 and 5.88 ± 5.11, respectively. The receiver operating characteristic (ROC) curve showed that the sensitivity and specificity for distinguishing SINRSBs from malignant nodules were 65% and 66% for KUR values &gt;6, respectively, with an area under the curve (AUC) of 0.709 (p&lt;0.0001). The MEN SKW values of the SINRSBs and malignant nodules were 1.73 ± 0.94 and 2.07 ± 1.01, respectively. The ROC curve showed that the sensitivity and specificity for distinguishing malignant nodules from SINRSBs were 65% and 66% for SKW values &gt;3.1, respectively, with an AUC of 0.709 (p&lt;0.0001). An analysis of the peak and plateau histograms revealed sensitivity, specificity, and accuracy values of 84%, 74%, and 79%, respectively. Conclusions. 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The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures. Objectives. The present study evaluated solid indeterminate nodules with a radiological stability suggesting benignity (SINRSBs) through a texture analysis of computed tomography (CT) images. Methods. A total of 100 chest CT scans were evaluated, including 50 cases of SINRSBs and 50 cases of malignant nodules. SINRSB CT scans were performed using the same noncontrast enhanced CT protocol and equipment; the malignant nodule data were acquired from several databases. The kurtosis (KUR) and skewness (SKW) values of these tests were determined for the whole volume of each nodule, and the histograms were classified into two basic patterns: peaks or plateaus. Results. The mean (MEN) KUR values of the SINRSBs and malignant nodules were 3.37 ± 3.88 and 5.88 ± 5.11, respectively. The receiver operating characteristic (ROC) curve showed that the sensitivity and specificity for distinguishing SINRSBs from malignant nodules were 65% and 66% for KUR values &gt;6, respectively, with an area under the curve (AUC) of 0.709 (p&lt;0.0001). The MEN SKW values of the SINRSBs and malignant nodules were 1.73 ± 0.94 and 2.07 ± 1.01, respectively. The ROC curve showed that the sensitivity and specificity for distinguishing malignant nodules from SINRSBs were 65% and 66% for SKW values &gt;3.1, respectively, with an AUC of 0.709 (p&lt;0.0001). An analysis of the peak and plateau histograms revealed sensitivity, specificity, and accuracy values of 84%, 74%, and 79%, respectively. Conclusions. KUR, SKW, and histogram shape can help to noninvasively diagnose SINRSBs but should not be used alone or without considering clinical data.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>31687208</pmid><doi>10.1155/2019/4071762</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-8598-4878</orcidid><orcidid>https://orcid.org/0000-0003-0423-2514</orcidid><orcidid>https://orcid.org/0000-0002-0732-3713</orcidid><orcidid>https://orcid.org/0000-0001-6687-5836</orcidid><oa>free_for_read</oa></addata></record>
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source Wiley-Blackwell Open Access Collection; Publicly Available Content Database; PubMed Central
subjects Algorithms
Archives & records
Clinical medicine
CT imaging
Diagnosis, Differential
Endoscopy
Humans
Image databases
Image Processing, Computer-Assisted
Kurtosis
Lung cancer
Lung Neoplasms - diagnostic imaging
Medical imaging
Models, Statistical
Mortality
R&D
Research & development
Retrospective Studies
Sensitivity and Specificity
Skewness
Software
Solitary Pulmonary Nodule - diagnostic imaging
Specific gravity
Tomography, X-Ray Computed
title Solid Indeterminate Nodules with a Radiological Stability Suggesting Benignity: A Texture Analysis of Computed Tomography Images Based on the Kurtosis and Skewness of the Nodule Volume Density Histogram
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