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

IF 2 Q3 RESPIRATORY SYSTEM
Bruno Max Borguezan, A. Lopes, E. H. Saito, Claudio C. Higa, A. Silva, R. Nunes
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引用次数: 3

Abstract

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 (p < 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 >3.1, respectively, with an AUC of 0.709 (p < 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.
具有放射学稳定性提示良性的固体不确定结节:基于结节体积密度直方图峰度和偏度的计算机断层图像纹理分析
背景利用影像学方法诊断其他胸部或胸外疾病时偶然发现肺结节的数量有所增加,这表明需要深入的影像学分析来识别结节类型并避免不必要的侵入性手术。目的:本研究通过计算机断层扫描(CT)图像的纹理分析,评估具有放射学稳定性提示良性的固体不确定结节(SINRSBs)。方法对100例胸部CT片进行评价,其中SINRSBs 50例,恶性结节50例。采用相同的非对比增强CT方案和设备进行SINRSB CT扫描;恶性结节的资料来源于多个数据库。测定每个结节整个体积的峰度(KUR)和偏度(SKW)值,并将直方图分为两种基本模式:峰值或平台。结果SINRSBs和恶性结节的平均(MEN) KUR值分别为3.37±3.88和5.88±5.11。受试者工作特征(ROC)曲线显示,当KUR值>6时,sinrsb与恶性结节区分的敏感性为65%,特异性为66%,曲线下面积(AUC)为0.709 (p < 0.0001)。sinrsb和恶性结节的MEN SKW值分别为1.73±0.94和2.07±1.01。ROC曲线显示,SKW值>3.1时,区分恶性结节与SINRSBs的敏感性为65%,特异性为66%,AUC为0.709 (p < 0.0001)。峰值和平台直方图的分析显示,灵敏度、特异性和准确性分别为84%、74%和79%。结论KUR、SKW和直方图形状有助于无创诊断SINRSBs,但不应单独使用或不考虑临床资料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pulmonary Medicine
Pulmonary Medicine RESPIRATORY SYSTEM-
CiteScore
10.20
自引率
0.00%
发文量
4
审稿时长
14 weeks
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