肺结节良恶性鉴别特征及恶性磨玻璃结节浸润程度的鉴别诊断指标分析

林卫勇, 翁文俊

林卫勇, 翁文俊. 肺结节良恶性鉴别特征及恶性磨玻璃结节浸润程度的鉴别诊断指标分析[J]. 实用临床医药杂志, 2023, 27(24): 14-19. DOI: 10.7619/jcmp.20232071
引用本文: 林卫勇, 翁文俊. 肺结节良恶性鉴别特征及恶性磨玻璃结节浸润程度的鉴别诊断指标分析[J]. 实用临床医药杂志, 2023, 27(24): 14-19. DOI: 10.7619/jcmp.20232071
LIN Weiyong, WENG Wenjun. Identification characteristic of benign and malignant pulmonary nodules and differential diagnostic indicators of the infiltration degree of malignant ground-glass nodules[J]. Journal of Clinical Medicine in Practice, 2023, 27(24): 14-19. DOI: 10.7619/jcmp.20232071
Citation: LIN Weiyong, WENG Wenjun. Identification characteristic of benign and malignant pulmonary nodules and differential diagnostic indicators of the infiltration degree of malignant ground-glass nodules[J]. Journal of Clinical Medicine in Practice, 2023, 27(24): 14-19. DOI: 10.7619/jcmp.20232071

肺结节良恶性鉴别特征及恶性磨玻璃结节浸润程度的鉴别诊断指标分析

详细信息
    通讯作者:

    翁文俊, E-mail: wwjlyj284@163.com

  • 中图分类号: R734.2;R563;R445

Identification characteristic of benign and malignant pulmonary nodules and differential diagnostic indicators of the infiltration degree of malignant ground-glass nodules

  • 摘要:
    目的 

    探讨鉴别肺结节良恶性的临床特征、CT影像特征以及诊断恶性磨玻璃结节(GGN)浸润程度的指标。

    方法 

    选取行胸腔镜手术治疗的205例肺结节患者作为研究对象, 根据术后病理结果分为良性结节组、恶性结节组,分析2组患者的临床特征、影像学特征。根据术后病理结果(浸润程度),将恶性GGN患者进一步分为侵袭前病变(PL)组、微浸润性腺癌(MIA)组、浸润性腺癌(IAC)组,进行定量分析和定性分析,筛选恶性GGN浸润程度的独立影响因素并评估其诊断价值。

    结果 

    良性结节组与恶性结节组的结节位置、结节类型、胸膜凹陷征、血管集束征比较,差异有统计学意义(P < 0.05); 多因素Logistic回归分析结果显示,结节类型、胸膜凹陷征、血管集束征均为肺结节良恶性的独立影响因素(P < 0.05)。PL组与MIA组年龄、血管集束征、结节长径、平均CT值、结节类型比较,差异有统计学意义(P < 0.05); MIA组与IAC组结节长径、平均CT值、实性成分长径、血管集束征、胸膜凹陷征比较,差异有统计学意义(P < 0.05); 多因素Logistic回归分析结果显示,结节长径、平均CT值为恶性GGN浸润程度的独立影响因素(P < 0.05)。受试者工作特征曲线分析结果显示,结节长径、平均CT值单独鉴别诊断PL与MIA的曲线下面积(AUC)分别为0.805、0.857, 截断值分别为7.2 mm、-612.3 HU, 两者联合鉴别诊断的AUC为0.923; 结节长径、平均CT值单独鉴别诊断MIA与IAC的AUC分别为0.860、0.703, 截断值分别为16.2 mm、-338.1 HU, 两者联合鉴别诊断的AUC为0.893。

    结论 

    对于GGN, 特别是存在胸膜凹陷征、血管集束征者,应高度怀疑恶性肺结节的可能。肺结节长径、平均CT值均对恶性GGN浸润程度具有一定鉴别诊断价值,且两者联合应用的价值更高。

    Abstract:
    Objective 

    To investigate the clinical features, CT imaging features of benign and malignant pulmonary nodules, as well as the indicators for diagnosing the infiltration degree of malignant ground-glass nodules (GGN).

    Methods 

    A total of 205 patients with pulmonary nodules who underwent thoracoscopic surgery were selected as research subjects. According to the postoperative pathological results, they were divided into benign nodule group and malignant nodule group. The clinical features and imaging features of the two groups were analyzed. Based on the postoperative pathological results (infiltration degree), the patients with malignant GGN were further divided into preinvasive lesion (PL) group, minimally invasive adenocarcinoma (MIA) group, and invasive adenocarcinoma (IAC) group. Quantitative and qualitative analyses were conducted to screen for independent influencing factors of malignant GGN infiltration degree and evaluate their diagnostic value.

    Results 

    There were significant differences in nodule location, nodule type, pleural indentation sign, and vascular clustering sign between the benign nodule group and the malignant nodule group (P < 0.05). Multivariate Logistic regression analysis showed that nodule type, pleural indentation sign, and vascular clustering sign were independent influencing factors of benign and malignant pulmonary nodules (P < 0.05). There were significant differences in age, vascular clustering sign, nodule length, average CT value, and nodule type between the PL group and the MIA group (P < 0.05); there were significant differences in nodule length, average CT value, solid component length, vascular clustering sign, and pleural indentation sign between the MIA group and the IAC group (P < 0.05). Multivariate Logistic regression analysis showed that nodule length and average CT value were independent influencing factors of malignant GGN infiltration degree (P < 0.05). The receiver operating characteristic curve analysis showed that the area under the curve (AUC) of nodule length and average CT value for differential diagnosis of PL and MIA were 0.805 and 0.857, respectively, with cutoff values of 7.2 mm and -612.3 HU, respectively. The AUC of their combined diagnosis was 0.923; the AUC of nodule length and average CT value for differential diagnosis of MIA and IAC were 0.860 and 0.703, respectively, with cutoff values of 16.2 mm and -338.1 HU, respectively. The AUC of their combined diagnosis was 0.893.

    Conclusion 

    For GGN, especially those with pleural indentation sign and vascular clustering sign, a high suspicion of malignant pulmonary nodules should be raised. The length and average CT value of pulmonary nodules have certain diagnostic value for the infiltration degree of malignant GGN, and their combined application has higher diagnostic value.

  • 图  1   结节长径、平均CT值单独及联合鉴别诊断恶性GGN浸润程度的ROC曲线

    A: PL与MIA; B: MIA与IAC。

    表  1   良性结节组与恶性结节组患者临床资料比较(x±s)[n(%)]

    指标 分类 良性结节组(n=32) 恶性结节组(n=173) t/χ2 P
    年龄/岁 60.3±9.0 61.2±10.2 -0.557 0.578
    性别 16(50.0) 66(38.2) 1.580 0.209
    16(50.0) 107(61.8)
    高血压病 14(43.8) 64(37.0) 0.523 0.470
    18(56.2) 109(63.0)
    糖尿病 5(15.6) 21(12.1) 0.065 0.799
    27(84.4) 152(87.9)
    肿瘤史 1(3.1) 15(8.7) 0.512 0.474
    31(96.9) 158(91.3)
    结节类型 纯磨玻璃结节 0 14(8.1) 21.115 < 0.001
    混合性磨玻璃结节 8(25.0) 103(59.5)
    实性结节 24(75.0) 56(32.4)
    结节长径/mm 14.8±5.8 17.3±7.6 -1.133 0.259
    结节短径/mm 11.2±4.4 13.2±6.3 -1.178 0.087
    胸膜凹陷征 10(31.2) 99(57.2) 7.318 0.007
    22(68.8) 74(42.8)
    结节形态 分叶征 11(34.4) 84(48.6) 2.184 0.139
    毛刺征 3(9.4) 40(23.1) 3.079 0.079
    血管集束征 11(34.4) 117(67.6) 12.734 < 0.001
    21(65.6) 56(32.4)
    结节位置 左上叶 4(12.5) 45(26.0) 10.108 0.039
    左下叶 13(40.6) 30(17.4)
    右上叶 10(31.3) 63(36.4)
    右中叶 2(6.2) 8(4.6)
    右下叶 3(9.4) 27(15.6)
    下载: 导出CSV

    表  2   肺结节良恶性的多因素Logistic回归分析结果

    变量 回归系数 标准误 Wals P OR 95%CI
    结节位置 0.108 0.162 0.442 0.506 1.114 0.810~1.532
    结节类型 0.927 0.252 13.511 <0.001 2.526 1.541~4.141
    胸膜凹陷征 1.063 0.464 5.259 0.022 2.895 1.167~7.180
    血管集束征 0.971 0.441 4.841 0.028 2.641 1.112~6.272
    常量 -1.211 0.708 2.924 0.087 0.298
    下载: 导出CSV

    表  3   不同浸润程度恶性GGN患者的临床资料比较(x±s)[n(%)]

    指标 分类 PL组(n=11) MIA组(n=45) IAC组(n=61) PL组对比MIA组 MIA组对比IAC组
    t/χ2 P t/χ2 P
    年龄/岁 51.9±12.0 59.6±9.7 62.3±9.9 -2.252 0.028 -1.400 0.165
    性别 2(18.2) 14(31.1) 29(47.5) 0.229 0.632 2.899 0.089
    9(81.8) 31(68.9) 32(52.5)
    结节位置 左上叶 4(36.3) 8(17.8) 17(27.9) 4.999* 0.256* 3.210 0.546
    左下叶 2(18.2) 7(15.6) 7(11.5)
    右上叶 3(27.3) 20(44.4) 26(42.6)
    右中叶 2(18.2) 3(6.6) 1(1.6)
    右下叶 0 7(15.6) 10(16.4)
    结节长径/mm 8.2±2.1 11.6±3.7 19.5±7.0 -2.922 0.005 -6.888 < 0.001
    平均CT值/HU -627.3±75.6 -472.4±127.2 -352.1±176.1 -3.859 < 0.001 -3.892 < 0.001
    实性成分长径/mm 4.4±1.4 10.1±3.6 -10.065 < 0.001
    胸膜凹陷征 1(9.1) 13(28.9) 42(68.9) 0.943 0.332 15.567 < 0.001
    10(90.9) 32(71.1) 19(31.1)
    结节形态 分叶征 0 13(28.9) 29(47.5) 2.676 0.102 3.766 0.052
    毛刺征 0 2(4.4) 10(16.4) 1.000* 3.683 0.055
    血管集束征 1(9.1) 23(51.1) 50(82.0) 4.773 0.029 11.500 0.001
    10(90.9) 22(48.9) 11(18.0)
    结节类型 pGGO 11(100.0) 3(6.7) 0 36.240 < 0.001 0.074*
    mGGO 0 42(93.3) 61(100.0)
    *: Fisher确切概率法。
    下载: 导出CSV

    表  4   PL与MIA的多因素Logistic回归分析结果

    变量 回归系数 标准误 Wals P OR 95%CI
    结节长径 0.621 0.298 4.347 0.037 1.860 1.038~3.334
    平均CT值 0.019 0.008 5.849 0.016 1.019 1.004~1.034
    血管集束征 1.187 1.392 0.727 0.394 3.277 0.214~50.207
    年龄 0.072 0.053 1.866 0.172 1.075 0.969~1.191
    常量 2.113 4.040 0.273 0.601 8.272
    下载: 导出CSV

    表  5   MIA与IAC的多因素Logistic回归分析结果

    变量 回归系数 标准误 Wals P OR 95%CI
    结节长径 0.322 0.077 17.355 < 0.001 1.380 1.186~1.605
    平均CT值 0.006 0.002 6.899 0.009 1.006 1.001~1.010
    血管集束征 0.059 0.628 0.009 0.925 1.061 0.310~3.633
    胸膜凹陷征 1.014 0.554 3.359 0.067 2.758 0.932~8.161
    常量 -2.536 1.208 4.409 0.036 0.079
    下载: 导出CSV

    表  6   结节长径、平均CT值单独及联合应用对恶性GGN浸润程度的鉴别诊断效能

    变量 PL与MIA MIA与IAC
    AUC 敏感度 特异度 截断值 AUC 敏感度 特异度 截断值
    结节长径/mm 0.805 0.978 0.545 7.2 0.860 0.689 0.889 16.2
    平均CT值/HU 0.857 0.844 0.818 -612.3 0.703 0.492 0.844 -338.1
    联合 0.923 0.778 0.956 0.893 0.885 0.778
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-06-28
  • 修回日期:  2023-10-07
  • 网络出版日期:  2024-01-04
  • 刊出日期:  2023-12-27

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