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双层光谱探测器CT在鉴别肺腺癌与鳞状细胞癌中的诊断价值

Diagnostic value of dual-layer spectral detector CT in differentiating lung adenocarcinoma from squamous cell carcinoma.

作者信息

Mu Ronghua, Meng Zhuoni, Guo Zixuan, Qin Xiaoyan, Huang Guangyi, Yang Xuri, Jin Hui, Yang Peng, Deng Meimei, Zhang Xiaodi, Zhu Xiqi

机构信息

Department of Radiology, Graduate School of Guilin Medical University, Guilin, China.

Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China.

出版信息

Front Oncol. 2022 Dec 2;12:868216. doi: 10.3389/fonc.2022.868216. eCollection 2022.

Abstract

BACKGROUND AND OBJECTIVE

The pathological type of non-small cell lung cancer is considered to be an important factor affecting the treatment and prognosis. The purpose of this study was to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in determining efficacy to distinguish adenocarcinoma (AC) and squamous cell carcinoma (SC), and their combined diagnostic efficacy was also analyzed.

METHODS

This is a single-center prospective study, and we collected 70 patients with lung SC and 127 patients with lung AC confirmed by histopathological examination. Morphological parameters, plain scan CT value, biphasic enhanced CT value, and spectral parameters were calculated. The diagnostic efficiency of morphological parameters, spectral parameters, and spectral parameters combined with morphological parameters was obtained by statistical analysis.

RESULTS

In univariate analysis, seven morphological CT features differed significantly between SC and AC: tumor location (distribution), lobulation, spicule, air bronchogram, vacuole sign, lung atelectasis and/or obstructive pneumonia, and vascular involvement (all < 0.05). In the arterial phase and the venous phase, the spectral parameters of AC were higher than those of SC (AP-Zeff: 8.07 ± 0.23 vs. 7.85 ± 0.16; AP-ID: 1.41 ± 0.47 vs. 0.94 ± 0.28; AP-NID: 0.13 ± 0.04 vs. 0.09 ± 0.03; AP-λ: 3.42 ± 1.10 vs. 2.33 ± 0.96; VP-Zeff: 8.26 ± 0.23 vs. 7.96 ± 0.16; VP-ID: 1.18 ± 0.51 vs. 1.16 ± 0.30; VP-NID: 0.39 ± 0.13 vs. 0.29 ± 0.08; VP-λ: 4.42 ± 1.28 vs. 2.85 ± 0.72; < 0.001). When conducting multivariate analysis combining CT features and DLCT parameters with the best diagnostic efficacy, the independent predictors of AC were distribution on peripheral (OR, 4.370; 95% CI, 1.485-12.859; p = 0.007), presence of air bronchogram (OR, 5.339; 95% CI, 1.729-16.484; p = 0.004), and presence of vacuole sign ( OR, 7.330; 95% CI, 1.030-52.184; p = 0.047). Receiver operating characteristic curves of the SC and AC showed that VP-λ had the best diagnostic performance, with an area under the curve (AUC) of 0.864 and sensitivity and specificity rates of 85.8% and 74.3%, respectively; the AUC was increased to 0.946 when morphological parameters were combined, and sensitivity and specificity rates were 89.8% and 87.1%, respectively.

CONCLUSION

The quantitative parameters of the DLCT spectrum are of great value in the diagnosis of SC and AC, and the combination of morphological parameters and spectral parameters is helpful to distinguish SC from AC.

摘要

背景与目的

非小细胞肺癌的病理类型被认为是影响治疗和预后的重要因素。本研究旨在探讨双层光谱探测器计算机断层扫描(DLCT)的光谱参数在鉴别腺癌(AC)和鳞状细胞癌(SC)疗效方面的诊断价值,并分析其联合诊断效能。

方法

这是一项单中心前瞻性研究,我们收集了70例经组织病理学检查确诊的肺鳞状细胞癌患者和127例肺腺癌患者。计算形态学参数、平扫CT值、双期增强CT值和光谱参数。通过统计分析得出形态学参数、光谱参数以及光谱参数与形态学参数联合的诊断效能。

结果

单因素分析中,SC和AC之间的七个形态学CT特征存在显著差异:肿瘤位置(分布)、分叶、毛刺、空气支气管征、空泡征、肺不张和/或阻塞性肺炎以及血管受累(均P<0.05)。在动脉期和静脉期,AC的光谱参数高于SC(动脉期-Zeff:8.07±0.23对7.85±0.16;动脉期-ID:1.41±0.47对0.94±0.28;动脉期-NID:0.13±0.04对0.09±0.03;动脉期-λ:3.42±1.10对2.33±0.96;静脉期-Zeff:8.26±0.23对7.96±0.16;静脉期-ID:1.18±0.51对1.16±0.30;静脉期-NID:0.39±0.13对0.29±0.08;静脉期-λ:4.42±1.28对2.85±0.72;P<0.001)。当结合具有最佳诊断效能的CT特征和DLCT参数进行多因素分析时,AC的独立预测因素为外周分布(OR,4.370;95%CI,1.485-12.859;P=0.007)、空气支气管征的存在(OR,5.339;95%CI,1.729-16.484;P=0.004)和空泡征的存在(OR,7.330;95%CI,1.030-52.184;P=0.047)。SC和AC的受试者工作特征曲线显示,静脉期-λ具有最佳诊断性能,曲线下面积(AUC)为0.864,敏感性和特异性分别为85.8%和74.3%;当结合形态学参数时,AUC增加到0.946,敏感性和特异性分别为89.8%和87.1%。

结论

DLCT光谱的定量参数在SC和AC的诊断中具有重要价值,形态学参数和光谱参数的联合有助于区分SC和AC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4493/9755331/207b0f19576a/fonc-12-868216-g001.jpg

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