Spectral CT Combined with Tumor Markers to Predict Ki-67 Expression in Lung Adenocarcinoma
-
摘要:
目的：探讨能谱CT定量参数联合血清肿瘤标志物（CEA、CA-125）对肺腺癌Ki-67表达的预测价值。方法：回顾性分析2020年6月至2022年2月经病理证实为肺腺癌的64例患者临床病理及影像学资料，所有患者均行双期能谱CT检查，且疗前血清CEA和CA-125水平明确。根据术后病理结果分为Ki-67高表达组（＞30％）、Ki-67低表达组（≤30％）。经双能量后处理工作站测得能谱相关定量参数碘值（IC）、标准化碘比率（NIC）及能谱曲线斜率（λHU），根据病历资料获取疗前血清CEA和CA-125表达水平。采用t/Mann-Whitney U检验、
$\chi^2 $ 检验比较两组间各参数的差异，采用ROC曲线评估参数的预测效能。结果：Ki-67低表达组静脉期IC、NIC和λHU值均高于高表达组，组间差异有统计学意义；Ki-67高表达组血清CEA及CA-125水平高于低表达组，组间差异有统计学意义；其他参数组间差别无统计学意义。ROC曲线分析显示多因素联合指标对Ki-67的预测效能明显高于各单因素指标，曲线下面积为0.754，敏感度为77.78％，特异度为72.97％。结论：静脉期能谱CT定量参数、血清CEA及CA-125水平对预测Ki-67表达有一定价值，能够为临床治疗方案的选择提供一定依据。Abstract:Purpose: To investigate the predictive value of energy spectrum CT quantitative parameters combined with serum tumor markers (CEA, CA-125) on Ki-67 expression in lung adenocarcinoma. Methods: The clinicopathological and imaging data of 64 patients with lung adenocarcinoma confirmed by pathology from June 2020 to February 2022 were retrospectively analyzed. All patients underwent dual-phase energy spectrum CT examination, and serum CEA and CA-125 levels before treatment were clear. Based on postoperative pathological results, patients were divided into two groups, the high expression group of Ki-67 (>30%) and the low expression group of Ki-67 (≤30%). The iodine value (IC), standardized iodine ratio (NIC), and the slope of the energy spectrum curve (λHU) were measured by a dual-energy post-processing workstation. The expression levels of SERUM CEA and CA-125 before treatment were obtained according to medical records. Statistical analysis of the data was performed with SPSS 22.0; t-test or Mann−Whitney U test and
$\chi^2 $ tests were used to compare the differences in parameters between the two groups, and the ROC (receiver operating characteristic curve, ROC) curve was used to evaluate the prediction efficiency of the parameters. Results: The IC, NIC, and λHU values in the low expression group were higher than those of the high expression group, and the differences were statistically significant. Serum CEA and CA-125 levels in the Ki-67 high expression group were higher than those of the low expression group, and the difference was statistically significant. There were no significant differences in other parameters between the two groups. ROC curve analysis showed that CEA had the best predictive efficiency for Ki-67, with an area under the curve of 0.697, sensitivity of 39.17%, and specificity of 100%. Conclusions: The quantitative parameters of energy spectrum CT in the venous phase, serum CEA, and CA12-5 levels have a certain value in predicting the expression of Ki-67, which can provide a basis for selecting a clinical treatment plan.-
Keywords:
- energy spectrum CT /
- lung adenocarcinoma /
- tumor markers /
- Ki-67
-
-
![]()
图 2 病例CT图像特征示意图，患者男，62岁，右肺下叶肺腺癌
Figure 2. Schematic diagram of CT images of one case. The patient is a 62-year-old male with adenocarcinoma of the lower lobe of the right lung
![]()
图 4 多因素联合指标预测Ki-67的ROC曲线分析
Figure 4. ROC curve analysis of multi-factor combined index prediction Ki-67
表 1 Ki-67高低表达组间临床及影像学特征比较（n=64）
Table 1 Comparison of clinical and imaging characteristics between the high and low Ki-67 expression groups (n=64)
项目 参数 例数（百分比） 低表达组 高表达组 P 性别 男性 31（48.4） 14 17 0.994 女性 33（51.6） 18 15 年龄（平均数/岁） ≤62 31（48.4） 18 13 0.604 ＞62 33（51.6） 14 19 结节或肿块/cm 结节（≤3） 30（46.9） 17 13 0.113 肿块（＞3） 34（53.1） 15 19 长径（中位数/mm） ≤32 34（53.1） 22 12 0.735 ＞32 30（46.9） 10 20 短径（中位数/mm） ≤23 32（50.0） 20 12 0.351 ＞23 32（50.0） 12 20 
下载: 导出CSV
表 2 高、低Ki-67表达组间能谱定量参数、血清肿瘤标志物水平比较（n=64）
Table 2 Comparison of quantitative parameters of the energy spectrum and serum tumor markers between the high and low Ki-67 expression groups (n=64)
项目 参数 低表达组$ (\bar x\pm s) $ 高表达组$ (\bar x\pm s) $ P 动脉期 IC 1.182±0.253 0.870±0.090 0.984 NIC 0.125±0.024 0.998±0.012 0.727 λHU 1.788±0.305 1.240±0.097 0.702 静脉期 IC 1.782±0.203 1.122±0.213 0.020 NIC 0.405±0.041 0.227±0.025 0.026 λHU 2.399±0.295 1.458±0.107 0.013 血清肿瘤标志物 CEA 12.081±3.375 42.468±11.322 0.032 CA-125 4.337±0.884 9.106±1.703 0.045 注：低表达组：Ki-67＜30％；高表达组：Ki-67≥30％；IC：碘值；NIC：标准化碘比率；λHU：40～100 keV之间的能谱衰减
曲线斜率；CEA：癌胚抗原；CA-125：糖类抗原；粗体表示高低Ki-67组间存在显著性差异（P＜0.05）。
下载: 导出CSV
表 3 能谱参数及血清肿瘤标志物水平预测Ki-67的效能
Table 3 Efficacy of energy spectrum parameters and serum tumor marker levels in predicting Ki-67
参数 AUC 截断值 敏感性/％ 特异性/％ P CEA 0.697 44.07 39.13 100.00 0.019 CA-125 0.688 5.26 52.17 88.24 0.026 *IC 0.669 1.00 48.39 81.82 0.014 *NIC 0.662 25.3 54.84 78.79 0.019 *λHU 0.680 1.19 41.94 93.94 0.008 注：CEA：癌胚抗原；CA-125：糖类抗原；*：静脉期；IC：碘值；NIC：标准化碘比率；λHU：40～100 keV之间的能谱衰减曲
线斜率。
下载: 导出CSV
表 4 多因素联合指标预测Ki-67的效能
Table 4 Prediction of Ki-67 performance by multiple factors combined with indicators
参数 AUC 敏感性/％ 特异性/％ P 联合指标 0.754 77.78 72.97 ＜0.01 注：联合指标：各项单因素指标（CEA、CA-125及静脉期IC、NIC、λHU）逻辑回归后所生成的多因素联合指标。
下载: 导出CSV
-
[1] TRAVIS W D, BRAMBILLA E, NOGUCHI M, et al. International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society: International multidisciplinary classification of lung adenocarcinoma[J]. Journal of Thoracic Oncology, 2011, 6(2): 244−285. doi: 10.1097/JTO.0b013e318206a221
[2] ZHANG J, WU J, TAN Q, et al. Why do pathological stage IA lung adenocarcinomas vary from prognosis? A clinicopathologic study of 176 patients with pathological stage IA lung adenocarcinoma based on the IASLC/ATS/ERS classification[J]. Journal of Thoracic Oncology, 2013, 8(9): 1196−1202. doi: 10.1097/JTO.0b013e31829f09a7
[3] 陈海瑞, 李文才, 陈天东, 等. 原发性肺腺癌组织亚型及预后[J]. 河南医学研究, 2017,26(18): 3271−3273. doi: 10.3969/j.issn.1004-437X.2017.18.003 CHEN H R, LI W C, CHEN T D, et al. Subtypes and prognosis of primary lung adenocarcinoma[J]. Henan Medical Research, 2017, 26(18): 3271−3273. (in Chinese). doi: 10.3969/j.issn.1004-437X.2017.18.003
[4] WARTH A, MULEY T, MEISTER M, et al. The novel histologic International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification system of lung adenocarcinoma is a stage-independent predictor of survival[J]. Journal of Clinical Oncology, 2012, 30(13): 1438−1446. doi: 10.1200/JCO.2011.37.2185
[5] ROSS D T, SCHERF U, EISEN M B, et al. Systematic variation in gene expression patterns in human cancer cell lines[J]. Nature Genetics, 2000, 24(3): 227. doi: 10.1038/73432
[6] MARTIN B, PAESMANS M, MASCAUX C, et al. Ki-67 expression and patients survival in lung cancer: Systematic review of the literature with meta-analysis[J]. British Journal of Cancer, 2004, 91(12): 2018−2025. doi: 10.1038/sj.bjc.6602233
[7] ISHIBASHI N, MAEBAYASHI T, AIZAWA T, et al. Correlation between the Ki-67 proliferation index and response to radiation therapy in small cell lung cancer[J]. Radiation Oncology, 2017, 12(16): 3−7.
[8] LI Y, PAN Y, WANG R, et al. ALK-rearranged lung cancer in Chinese: A comprehensive assessment of clinicopathology, IHC, FISH and RT-PCR[J]. Plos One, 2013, 8(7): e69016. doi: 10.1371/journal.pone.0069016
[9] TOMIYAMA N, YASUHARA Y, NAKAJIMA Y, et al. CT-guided needle biopsy of lung lesions: A survey of severe complication based on 9783 biopsies in Japan[J]. European Journal of Radiology, 2006, 59(1): 60−64. doi: 10.1016/j.ejrad.2006.02.001
[10] SHAN L, LIAN F, GUO L, et al. Detection of ROS1 gene rearrangement in lung adenocarcinoma: Comparison of IHC, FISH and Real-Time RT-PCR[J]. Plos One, 2015, 10(3): e0120422. doi: 10.1371/journal.pone.0120422
[11] THIEME S F, GRAUTE V, NIKOLAOU K, et al. Dual energy CT lung perfusion imaging: Correlation with SPECT/CT[J]. European Journal of Radiology, 2012, 81(2): 360−365. doi: 10.1016/j.ejrad.2010.11.037
[12] MCCOLLOUGH C H, LENG S, YU L, et al. Dual- and multi-energy CT: Principles, technical approaches, and clinical applications[J]. Radiology, 2015, 276(3): 637−653. doi: 10.1148/radiol.2015142631
[13] LI G J, GAO J, WANG G L, et al. Correlation between vascular endothelial growth factor and quantitative dual-energy spectral CT in non-small-cell lung cancer[J]. Clinical Radiology, 2016, 71(4): 363−368. doi: 10.1016/j.crad.2015.12.013
[14] KARCAALTINCABA M, AKTAS A. Dual-energy CT revisited with multidetector CT: Review of principles and clinical applications[J]. Diagnostic and Interventional Radiology, 2011, 17(3): 181−194.
[15] de CECCO C N, DARNELL A, RENGO M, et al. Dual-energy CT: Oncologic applications[J]. American Journal of Roentgenology, 2012, 199(l): 98−105.
[16] FORNARO J, LESCHKA S, HIBBELN D, et al. Dual- and multi-energy CT: Approach to functional imaging[J]. Insights Imaging, 2011, 2(2): 149e59.
[17] LIN L Y, ZHANG Y, SUO S T, et al. Correlation between dual-energy spectral CT imaging parameters and pathological grades of non-small cell lung cancer[J]. Clinical Radiology, 2018, 73(4): 412.e1−412.e7. doi: 10.1016/j.crad.2017.11.004
[18] YANG F, DONG J, WANG X, et al. Non-small cell lung cancer: Spectral computed tomography quantitative parameters for preoperative diagnosis of metastatic lymph nodes[J]. European Journal of Radiology, 2017, 89: 129−135.
[19] SALGIA R, HARPOLE D, HERNDON J A, et al. Role of serum tumor markers CA 125 and CEA in non-small cell lung cancer[J]. Anticancer Research, 2001, 21(2B): 1241−1246.
-
期刊类型引用(3)
1. 陈宗桂，陆思璇，董晓军，张英俊. 基于改进区域生长法分割CT图像肝肿瘤的研究. 电子设计工程. 2024(10): 180-185 . 
百度学术
2. 李柯，刘文忠，秦镜淘. 改进TransUNet网络对肝脏肿瘤CT图像的级联分割. 宜宾学院学报. 2024(12): 12-20 . 百度学术
3. 张敏，朱雨涵，王承心，陈玮容，陈新房. 基于混合网络与数字高程模型的遥感图像滑坡识别. 电脑与电信. 2024(11): 12-16 . 百度学术
其他类型引用(3)
计量
- 文章访问数: 250
- HTML全文浏览量: 79
- PDF下载量: 21
- 被引次数: 6
