Lin L-Y, Zhang Y, Suo S-T, Zhang F, Cheng J-J, Wu H-W
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160, Pujian Road, Shanghai, 200127, China.
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160, Pujian Road, Shanghai, 200127, China.
Clin Radiol. 2018 Apr;73(4):412.e1-412.e7. doi: 10.1016/j.crad.2017.11.004. Epub 2017 Dec 6.
To investigate the correlation between pathological grades of non-small cell lung cancers (NSCLCs) and quantitative parameters generated in dual-energy spectral computed tomography (CT).
Fifty-three patients with NSCLCs who underwent preoperative dual-energy spectral CT imaging and surgical resection were evaluated retrospectively. These patients were divided into a low-grade group and a high-grade group based on their histopathological differentiation. In the arterial phase (AP) and venous phase (VP), iodine concentration (IC) in cancers was measured in iodine-based material decomposition images, and normalised to the IC in the aorta to calculate the normalised iodine concentration (NIC), the spectral CT curve was generated from the monochromatic images to calculate the slope of the spectral curve (λ). Differences in quantitative parameters (NIC and λ) were compared using the two-sample t-test. The correlations between spectral CT parameters and tumour grades were evaluated using the Spearman rank correlation analysis. Receiver operating characteristic (ROC) curves were generated to calculate their diagnostic efficacies.
The NIC and λ in the low-grade NSCLC group were significantly higher than those in the high-grade NSCLC group both in AP and VP (all p<0.001). There was a significant negative correlation between spectral CT parameters and pathological grades by the Spearman rank correlation (all p<0.001). ROC analysis indicated that λ in VP provided the best diagnostic performance in distinguishing high-grade cancers from low-grade cancers (area under the ROC curve [AUC], 0.914; sensitivity, 85.7%; specificity, 84.4%).
The quantitative parameters in dual-energy spectral CT imaging provide useful information to differentiate the pathological grades of NSCLCs.
探讨非小细胞肺癌(NSCLC)的病理分级与双能谱计算机断层扫描(CT)所生成的定量参数之间的相关性。
回顾性评估53例接受术前双能谱CT成像及手术切除的NSCLC患者。根据组织病理学分化情况将这些患者分为低级别组和高级别组。在动脉期(AP)和静脉期(VP),于碘基物质分解图像中测量癌灶内的碘浓度(IC),并将其标准化为主动脉内的IC以计算标准化碘浓度(NIC),从单色图像生成光谱CT曲线以计算光谱曲线斜率(λ)。使用两样本t检验比较定量参数(NIC和λ)的差异。采用Spearman等级相关分析评估光谱CT参数与肿瘤分级之间的相关性。绘制受试者工作特征(ROC)曲线以计算其诊断效能。
低级别NSCLC组在AP和VP中的NIC及λ均显著高于高级别NSCLC组(均p<0.001)。Spearman等级相关分析显示光谱CT参数与病理分级之间存在显著负相关(均p<0.001)。ROC分析表明,VP中的λ在区分高级别癌与低级别癌方面具有最佳诊断性能(ROC曲线下面积[AUC]为0.914;灵敏度为85.7%;特异度为84.4%)。
双能谱CT成像中的定量参数为鉴别NSCLC的病理分级提供了有用信息。