Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea.
Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
PLoS One. 2018 Nov 26;13(11):e0207959. doi: 10.1371/journal.pone.0207959. eCollection 2018.
To evaluate the feasibility of quantitative analysis of chest computed tomography (CT) scans for the assessment of lymph node (LN) involvement in patients with pulmonary tuberculosis and sarcoidosis.
In 47 patients with tuberculosis (n = 26) or sarcoidosis (n = 21), 115 lymph nodes (tuberculous, 55; sarcoid, 60) were visually analyzed on chest CT scans according to their size, location, attenuation and shape. Each node was manually segmented using image analysis tool, which was quantitatively analyzed using the following variables: Feret's diameter, perimeter, area, circularity, mean grey value (Mean), standard deviation (SD) of grey value, minimum grey value (Min), maximum grey value (Max), median grey value (Median), skewness, kurtosis, and net enhancement. We statistically analyzed the visual and quantitative CT features of tuberculous and sarcoid LNs.
In visual CT analysis, the mean node size in sarcoidosis was significantly greater than that in tuberculosis. There were no statistical differences between tuberculous and sarcoid LNs in terms of location and shape. Central low attenuation and peripheral rim enhancement were more frequently observed in tuberculous LNs than in the sarcoid ones. In quantitative CT analysis, there were significant differences in the values of the Feret's diameter, perimeter, area, circularity, mean grey value, SD, median, skewness, and kurtosis between tuberculous and sarcoid LNs.
Quantitative CT analysis using CT parameters with pixel-by-pixel measurements can help to differentiate of tuberculous and sarcoid LNs.
评估胸部计算机断层扫描(CT)定量分析在评估肺结核和结节病患者淋巴结(LN)受累的可行性。
在 47 例肺结核(n=26)或结节病(n=21)患者中,根据大小、位置、衰减和形状对胸部 CT 扫描中的 115 个淋巴结(结核性,55 个;结节病性,60 个)进行视觉分析。使用图像分析工具手动对每个节点进行分割,使用以下变量对其进行定量分析:Feret 直径、周长、面积、圆形度、平均灰度值(Mean)、灰度值标准差(SD)、最小灰度值(Min)、最大灰度值(Max)、灰度值中位数(Median)、偏度、峰度和净增强。我们对结核性和结节性 LN 的视觉和定量 CT 特征进行了统计学分析。
在视觉 CT 分析中,结节病中淋巴结的平均大小明显大于肺结核。结核性和结节性 LN 在位置和形状方面无统计学差异。中央低衰减和周围边缘强化在结核性 LN 中比在结节性 LN 中更常见。在定量 CT 分析中,结核性和结节性 LN 的 Feret 直径、周长、面积、圆形度、平均灰度值、SD、中位数、偏度和峰度值存在显著差异。
使用像素级测量的 CT 参数进行定量 CT 分析有助于区分结核性和结节性 LN。