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Multidetector CT features of pulmonary focal ground-glass opacity: Differences between benign and malignant

机译:肺局灶性玻璃样混浊的多探测器CT特征:良性与恶性之间的差异

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Objective: To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT). Methods: 82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ 2 test, Fisher's exact test or Mann-Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy. Results: There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively. Conclusion: An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant.
机译:目的:通过多探测器CT(MDCT)评价良性和恶性肺局灶性玻璃体混浊(fGGO)的不同特征。方法:回顾性分析82例经病理或临床证实的fGGOs的人口统计学数据,病变大小和位置,衰减值和MDCT特征,包括形状,边缘,界面,内部特征和邻近结构。使用χ2检验,Fisher精确检验或Mann-Whitney U检验分析良性和恶性fGGO之间的差异。通过二进制逻辑回归分析分析形态特征,以估计恶性肿瘤的可能性。结果:良性病变21例,恶性病变61例。在人口统计学数据,大小,位置和衰减值方面,在良性和恶性fGGO之间未发现统计学差异。小叶形成的频率(p = 0.000),针刺形成的频率(p = 0.008),脊柱样突突(p = 0.004),轮廓分明但粗糙的界面(p = 0.000),支气管截止(p = 0.003),其他恶性fGGO的气密空间(p = 0.000),胸膜压痕(p = 0.000)和血管收敛(p = 0.006)明显高于良性fGGO。二元逻辑回归分析表明,小叶,界面和胸膜压痕是fGGO恶性诊断的重要指标,相应的比值比分别为8.122、3.139和9.076。此外,定义明确但粗糙的界面是所有界面类型中最重要的恶性指标。考虑到所有三个重要指标,诊断敏感性,特异性和准确性分别为93.4%,66.7%和86.6%。结论:具有小叶,清晰但粗糙的界面和胸膜凹痕的fGGO较恶性肿瘤的可能性要高。

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