基于能谱CT参数与临床病理因素建立高海拔地区非小细胞肺癌患者的淋巴结转移预测模型

胡志鹏, 冶治, 张庆欣

胡志鹏, 冶治, 张庆欣. 基于能谱CT参数与临床病理因素建立高海拔地区非小细胞肺癌患者的淋巴结转移预测模型[J]. 实用临床医药杂志, 2022, 26(18): 6-10. DOI: 10.7619/jcmp.20220739
引用本文: 胡志鹏, 冶治, 张庆欣. 基于能谱CT参数与临床病理因素建立高海拔地区非小细胞肺癌患者的淋巴结转移预测模型[J]. 实用临床医药杂志, 2022, 26(18): 6-10. DOI: 10.7619/jcmp.20220739
HU Zhipeng, YE Zhi, ZHANG Qingxin. Establishment of a prediction model of lymph node metastasis in patients with non-small cell lung cancer at high altitude areas based on energy spectrum CT parameters and clinicopathological factors[J]. Journal of Clinical Medicine in Practice, 2022, 26(18): 6-10. DOI: 10.7619/jcmp.20220739
Citation: HU Zhipeng, YE Zhi, ZHANG Qingxin. Establishment of a prediction model of lymph node metastasis in patients with non-small cell lung cancer at high altitude areas based on energy spectrum CT parameters and clinicopathological factors[J]. Journal of Clinical Medicine in Practice, 2022, 26(18): 6-10. DOI: 10.7619/jcmp.20220739

基于能谱CT参数与临床病理因素建立高海拔地区非小细胞肺癌患者的淋巴结转移预测模型

基金项目: 

青海省科技计划项目 2019-ZJ-931

详细信息
  • 中图分类号: R734.2;R445

Establishment of a prediction model of lymph node metastasis in patients with non-small cell lung cancer at high altitude areas based on energy spectrum CT parameters and clinicopathological factors

  • 摘要:
    目的 

    探讨高海拔地区非小细胞肺癌(NSCLC)患者的淋巴结转移的能谱CT参数、临床病理因素、影响因素及其预测模型的应用效能。

    方法 

    选取青海省人民医院2020年1月—2021年7月收治的84例NSCLC患者作为研究对象,其中50例患者进行能谱CT检测并收集临床资料。依据淋巴结转移病理检查结果将50例患者分为转移组、未转移组,采用单因素分析2组患者的临床病理因素、能谱CT参数差异,采用多因素回归分析NSCLC患者发生淋巴结转移的影响因素并建立预测模型。应用预测模型分析其他34例NSCLC患者的淋巴结转移情况,以临床检测结果为金标准,评估预测模型的应用价值。

    结果 

    ① 50例患者的淋巴结转移发生率为30.00%。转移组患者的术前癌胚抗原(CEA)、中央型隆突位置比率、淋巴结直径高于未转移组,差异有统计学意义(P < 0.05)。②转移组患者的淋巴结能谱曲线斜率(λHu)、标准化碘密度值(NIC)、淋巴结与原发病灶的λHu比值均低于未转移组,差异有统计学意义(P < 0.05)。③ NSCLC患者发生淋巴结转移的危险因素为淋巴结与原发病灶的λHu比值、术前CEA≥5 ng/mL、淋巴结直径≥3 cm。④ NSCLC患者淋巴结转移的预测模型诊断34例NSCLC患者的准确度、特异度、敏感度均在80.00%以上。

    结论 

    NSCLC患者淋巴结转移中可应用能谱CT参数以及临床病理因素中的相关危险因素建立预测模型进行准确预测,该模型可作为预测淋巴结转移的首选工具。

    Abstract:
    Objective 

    To explore the energy spectrum CT parameters, clinicopathological factors, influencing factors and the application efficiency of the prediction model of lymph node metastasis in patients with non-small cell lung cancer (NSCLC) at high altitude area.

    Methods 

    A total of 84 NSCLC patients from January 2020 to July 2021 in Qinghai Provincial People′s Hospital were selected as research objects, of whom 50 patients were conducted with energy spectrum CT detection and their clinical materials were collected. According to the pathological examination results of lymph node metastasis, 50 patients were divided into metastasis group and non-metastasis group, the differences of clinicopathological factors and energy spectrum CT parameters between the two groups were analyzed by univariate analysis, the influencing factors of lymph node metastasis in NSCLC patients were analyzed by multivariate regression analysis, and a prediction model was established. The prediction model was used to analyze the lymph node metastasis of the other 34 NSCLC patients, and the clinical test results were used as the gold standard to evaluate the application value of the prediction model.

    Results 

    ① The incidence of lymph node metastasis in 50 patients was 30.00%. The preoperative carcinoembryonic antigen (CEA), ratio of central carina position and lymph node diameter in the metastasis group were significantly higher than those in the non-metastasis group (P < 0.05). ② Slope of energy spectrum curve of lymph nodes (λHu), normalized iodine concentration (NIC) and λHu ratio of lymph nodes to primary lesions in the metastasis group were significantly lower than those in the non-metastasis group (P < 0.05). ③ The risk factors of lymph node metastasis in NSCLC patients were the λHu ratio of lymph nodes to primary lesions, preoperative CEA≥5 ng/mL and lymph node diameter≥3 cm. ④ The accuracy, specificity and sensitivity of the prediction model for lymph node metastasis in 34 patients with NSCLC were all above 80.00%.

    Conclusion 

    In the NSCLC patients with lymph node metastasis, energy spectrum CT parameters and related risk factors in clinicopathological factors can be used to establish a prediction model for accurate prediction, and this model can be used as the preferred tool to predict lymph node metastasis.

  • 图  1   NSCLC患者淋巴结转移的影像检查结果

    A: 中央型鳞癌,肿瘤侵犯上腔静脉,纵隔淋巴结转移; B: 上叶支气管完全阻塞,右上叶完全不张; C: 肺门淋巴结及隆突下淋巴结明显增大,考虑转移; D: 肿瘤侵犯右侧主肺动脉; E: 肿瘤侵犯右肺上叶尖前干支动脉。

    图  2   多元线性回归方程标准化残差直方图

    表  1   NSCLC患者淋巴结转移临床特征的单因素分析[n(%)]

    临床特征   分类 转移组(n=15) 未转移组(n=35) χ2 P
    年龄 < 60岁 6(40.00) 16(45.71) 0.139 0.709
    ≥60岁 9(60.00) 19(54.29)
    性别 5(33.33) 16(45.71) 0.661 0.416
    10(66.67) 19(54.29)
    术前癌胚抗原 < 5 ng/mL 3(20.00) 24(68.57) 9.972 0.002
    ≥5 ng/mL 12(80.00) 11(31.43)
    淋巴结直径 < 3 cm 4(26.67) 22(62.86) 5.510 0.019
    ≥3 cm 11(73.33) 13(37.14)
    距隆突位置 中央型 10(66.67) 10(28.57) 6.349 0.012
    周围型 5(33.33) 25(71.43)
    吸烟史 7(46.67) 16(45.71) 0.004 0.951
    8(53.33) 19(54.29)
    下载: 导出CSV

    表  2   转移组与未转移组能谱CT参数比较(x±s)

    参数 转移组(n=15) 未转移组(n=35)
    淋巴结λHu 1.82±0.57* 2.22±0.27
    原发病灶λHu 1.71±0.47 1.67±0.43
    淋巴结与原发病灶的λHu比值 1.02±0.22* 1.32±0.49
    Neff-Z 0.79±0.02 0.78±0.02
    IC 17.82±3.23 17.22±3.27
    WC 1.00±0.01 1.00±0.02
    NIC 0.22±0.02* 0.72±0.09
    NWC 1.02±0.01 1.02±0.02
    λHu: 能谱曲线斜率; Neff-Z: 标化有效原子序数; IC: 碘密度值; WC: 水密度值; NIC: 标准化碘密度值; NWC: 标准化水密度值。与未转移组比较, *P < 0.05。
    下载: 导出CSV

    表  3   变量赋值表

    变量 编号 赋值
    隆突位置 X1 1=中央型, 2=周围型
    术前CEA X2 1=≥5 ng/mL, 2= < 5 ng/mL
    淋巴结直径 X3 1=≥3 cm, 2= < 3 cm
    淋巴结λHu X4
    淋巴结与原发病灶的λHu比值 X5
    NIC X6
    淋巴结转移 Y 1=是, 2=否
    CEA: 癌胚抗原; λHu: 能谱曲线斜率; NIC: 标准化碘密度值。
    下载: 导出CSV

    表  4   多因素分析NSCLC患者淋巴结转移的影响因素

    变量 非标准化系数 标准错误 标准系数 T P VIF
    常数 2.689 0.560 4.799 < 0.001
    术前CEA -0.403 0.115 -0.439 -3.497 0.001 1.055
    淋巴结直径 0.337 0.119 -0.367 -2.829 0.007 1.127
    距隆突位置 -0.088 0.127 -0.088 -0.688 0.495 1.085
    淋巴结与原发病灶的λHu比值 0.463 0.174 -0.419 -2.332 0.004 1.032
    淋巴结λHu -0.139 0.166 -0.107 -0.834 0.409 1.105
    NIC -0.132 0.161 -0.102 -0.828 0.411 1.102
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-03-07
  • 网络出版日期:  2022-10-23
  • 刊出日期:  2022-09-22

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