Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, No. 6 Jiefang St, Zhongshan District, Dalian Liaoning 116001, China.
Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
AJR Am J Roentgenol. 2019 Sep;213(3):W114-W122. doi: 10.2214/AJR.19.21245. Epub 2019 May 13.
The objective of our study was to investigate the potentials of enhanced dual-source dual-energy CT (DECT) and three-planar measurements for differentiating invasive pulmonary adenocarcinomas (IPAs) from preinvasive lesions appearing as pure ground-glass nodules (pGGNs). Thirty-nine patients with 53 pGGNs who underwent enhanced dual-source DECT were included in this retrospective study. All pGGNs were pathologically confirmed and categorized into two groups: preinvasive lesions or IPAs. The traditional CT features of the pGGNs were evaluated on unenhanced images. Quantitative parameters were measured on iodine-enhanced images of dual-source DECT in three planes, and both intra- and interobserver reproducibility analyses were performed to assess the measurement reproducibility of quantitative parameters. To identify significant factors for differentiating IPAs from preinvasive lesions, we performed logistic regression analysis and ROC curve analysis. For traditional CT features, only lesion size and unenhanced CT attenuation value showed significant differences between preinvasive lesions and IPAs ( < 0.05). Preinvasive lesions and IPAs exhibited significant differences in attenuation on virtual images, so-called "virtual HU" or "VHU," and the modified normalized iodine concentration (NIC) ( < 0.05), and both intra- and interobserver agreement for the quantitative measurements were excellent. Multivariate logistic regression analysis revealed that larger lesion size (adjusted odds ratio [OR], 3.65) and higher modified NIC (adjusted OR, 19.01) were significant differentiators of IPAs from preinvasive lesions ( < 0.05). ROC curve analysis revealed that modified NIC showed excellent performance (AUC, 0.924) and significantly higher performance than lesion size (AUC, 0.711) for differentiating IPAs from preinvasive lesions. In pGGNs, a lesion with a modified NIC value of more than 0.29 can be a very specific discriminator of IPAs from preinvasive lesions, and IPAs can be accurately and reliably differentiated from preinvasive lesions using enhanced dual-source DECT and three-planar measurements.
本研究旨在探讨增强双源双能 CT(DECT)和三平面测量在鉴别表现为纯磨玻璃结节(pGGN)的浸润性肺腺癌(IPA)与浸润前病变方面的潜力。本回顾性研究纳入了 39 例 53 个 pGGN 患者,所有 pGGN 均经病理证实,并分为两组:浸润前病变或 IPA。在未增强图像上评估 pGGN 的传统 CT 特征。在双源 DECT 的碘增强图像上测量定量参数,并进行内部和观察者间的可重复性分析,以评估定量参数的测量可重复性。为了确定区分 IPA 与浸润前病变的显著因素,我们进行了逻辑回归分析和 ROC 曲线分析。对于传统 CT 特征,只有病变大小和未增强 CT 衰减值在浸润前病变和 IPA 之间有显著差异(<0.05)。浸润前病变和 IPA 在虚拟图像上的衰减值,即所谓的“虚拟 HU”或“VHU”,以及改良后的标准化碘浓度(NIC)有显著差异(<0.05),定量测量的内部和观察者间一致性均非常好。多变量逻辑回归分析显示,较大的病变大小(调整后的优势比[OR],3.65)和较高的改良 NIC(调整后的 OR,19.01)是 IPA 与浸润前病变的显著鉴别因素(<0.05)。ROC 曲线分析显示,改良 NIC 表现出优异的性能(AUC,0.924),且明显优于病变大小(AUC,0.711),可用于鉴别 IPA 与浸润前病变。在 pGGN 中,改良 NIC 值大于 0.29 的病变可以非常特异地区分 IPA 与浸润前病变,并且可以使用增强双源 DECT 和三平面测量准确可靠地鉴别 IPA 与浸润前病变。