不同层厚CT定量参数对评价肺结节生长的影响

Jannatul Maoya Bashanti, Binjie Fu, Wangjia Li, M. A. Hossain, Fajin Lv
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摘要

本研究旨在探讨CT图像厚(5mm)和薄(1或0.625 mm)层厚度对评估肺结节生长的影响,以提高其诊断准确性。回顾性分析2016年10月至2019年10月251例肺结节患者的临床、CT资料及2例随访CT资料。病理证实为恶性结节,病理或随访证实为良性结节。两名放射科医师双盲评估两张随访CT的厚(5MM)和薄(≤1MM)图像上结节的CT特征(密度、形状、叶、边界)、最大直径和体积。定量数据采用单因素方差分析;定性资料采用X2检验或FISHER精确概率法;采用ROC曲线分析结节大小、体积及变化对良恶性病变的诊断价值。251例肺结节中,良性117例(46.6%),恶性134例(53.3%)。CT随访中,良、恶性肺结节的厚片体积、直径、薄片体积均有统计学差异(P<0.001)。相比之下,两组在厚切片图像上测量的直径相似(P=0.328)。良、恶性肺结节,薄层图像测量的直径、体积、变化均显著大于厚层图像数据(P<0.001)。ROC曲线显示体积的诊断效率高于直径。良恶性结节的CT表现在结节类型、密度变化、形态、分叶、胸膜回缩等方面均有显著差异。准确评估体积变化并结合CT特征有助于提高肺结节的诊断准确性。CT薄层(1mm)图像体积测量是评估肺结节变化的最佳定量参数。将体积变化与CT特征相结合有助于提高诊断的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules
We did this study to investigate the effect of thick (5mm) and thin (1 or 0.625 mm) slice thickness of CT images on evaluating pulmonary nodules' growth to improve their diagnostic accuracy. The clinical and CT data of 251 patients with lung nodules and two follow-up CTs from October 2016 to October 2019 were analyzed retrospectively. Malignant nodules were confirmed by pathology, and benign nodules were confirmed by pathology or follow-up. Two radiologists double-blindly assessed the CT features (density, shape, lobes, border), maximum diameter, and volume of nodules on the thick (5MM) and thin (≤1MM) images of two follow-up CTs. We use One-way analysis of variance for quantitative data; the X2 test or FISHER exact probability method was used for qualitative data; and the ROC curve was used to analyze the diagnostic power of nodule size, volume, and change in differentiating benign and malignant lesions. Among 251 pulmonary nodules, 117 (46.6%) benign nodules and 134 (53.3%) malignant nodules. During the CT follow-up, the volume measured on the thick-section image, the diameter, and the volume measured on the thin-section image were statistically different in benign and malignant lung nodules (P<0.001). In contrast, the diameter measured on the thick-section image was similar between these two groups (P=0.328). For benign and malignant pulmonary nodules, the diameter, volume, and change measured on the thin-section image were significantly larger than the thick-section image's data (P<0.001). The ROC curve showed that the diagnostic efficiency of volume was higher compared to the diameter. There were significant differences in nodule type, density change, shape, lobulation, and pleural retraction between benign and malignant nodules for CT features. Accurately assessing the volume changes combined with CT characteristics will help improve lung nodules' diagnosis accuracy. Volume measured on thin-section (1mm) CT images is the best quantitative parameter for assessing the change of pulmonary nodules. Combining Volume change with CT characteristics would help to improve the diagnostic accuracy.
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